Financial Statement Analysis and Valuation of Lerøy Seafood

MASTER THESIS COPENHAGEN BUSINESS SCHOOL NOVEMBER 2015 Financial Statement Analysis and Valuation of Lerøy Seafood Supervisor: Edward Vali, Copenhagen Business School Number of standard pages: 119 Number of characters: 232 638 Hand- in date: 09.11.2015 Alexander Skogvold CPR: Cand Merc. AEF Glenn- Patrick Duvfors CPR: Cand Merc. AEF

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Contents 1. Introduction and motivation...5 1.1 Problem statement...6 1.1.1 Sub questions...6 1.2 Methodology and structure...8 1.2.1 Data collection...8 1.2.2 Theories...8 1.2.3 Structure...9 1.3 Delimitations...10 2. LSG and the fish farming industry...11 2.1 LSG...11 2.2 The salmon farming industry...12 2.2.1 Historical development of global supply (production regions)...12 2.2.2 Markets...13 2.2.3 MAB, market concentration and licenses...14 2.2.4 Production of salmon...15 2.2.5 Cost structure...16 2.2.6 Historical profitability and the state of now...17 2.3 Historical events and share price development, LSG...18 2.4 Business concept and strategy...19 2.5 Value chain...20 2.6 Corporate structure...22 2.7 Group management and key board directors...25 2.8 Ownership...26 2.9 Financial performance and development...27 2.10 Introduction to peer group...28 3. Financial analysis...31 3.1 Accounting quality...31 3.1.2 Accounting principles...31 3.1.3 Potential red flags...31 3.2 Analytical income statement and balance sheet...32 3.2.1 Income statement...32 3.2.2 Balance sheet...33 3.3 Analysis of historical profitability, growth and performance...35 3.3.1 Operating result decomposition of ROIC...36 3.3.2 Profit margin...37 3.3.3 Turnover rate invested capital...40 2

3.3.4 Index and common-size analysis of Invested capital...41 3.3.5 FGEAR...42 3.3.6 SPREAD...43 3.4 ROE Owners perspective...43 3.5 Liquidity analysis...44 3.5.1 Short-term liquidity risk...44 3.5.2 Long-term liquidity...45 3.5 Conclusion financial analysis...47 4. Strategic analysis...48 4.1 VRIO analysis...48 Roe and smolt production...49 Farming and harvesting...49 Production and VAP...51 Sales and distribution...52 4.1.1 Summary VRIO analysis...54 4.2 Porter s five forces...54 4.2.1 Threat of new entrants...55 4.2.2 The power of suppliers...57 4.2.3 The power of buyers...58 4.2.4 The threat of substitutes...59 4.2.5 Rivalry among existing companies...59 4.2.6 Summary Porter s five forces...61 4.3 PESTEL analysis...62 4.3.1 Political and legal factors...62 4.3.2 Economic factors...64 4.3.3 Social Factors...65 4.3.4 Technological factors...66 4.3.5 Environmental factors...67 4.4 Salmon price...69 4.4.1 Supply...70 4.4.2 Biomass, feed sales and smolt release...72 4.4.3 Lack of space...74 4.4.4 Demand...75 4.4.6 Summary supply and demand...76 4.5 Connecting the analyses SWOT...77 5. Forecasting...78 5.1 Income statement...78 5.1.1 Salmon price forecast...79 5.1.2 Summary and conclusion salmon price...82 5.1.3 Forecasted harvest volumes...83 3

5.1.4 Sales premium...85 5.1.5 Summary revenue forecast...86 5.2 Forecasted operating costs...87 5.2.1 Cost of goods sold...87 5.2.2 Salaries and other personnel costs...88 5.2.3 Other operating costs...88 5.3 Other line items...88 5.4 Summary Income statement forecast...89 5.5 Balance sheet forecast...89 5.4.1 Non-current assets...90 5.4.2 Current assets...91 5.4.3 Non-interest bearing debt (current liabilities)...92 5.4.4 Net operating working capital...93 5.4.5 Summary balance sheet forecast...93 5.5 Forecast summary...94 6 Cost of capital...95 6.1 Capital structure...95 6.2 Cost of equity ( )...96 6.2.1 Conclusion cost of capital...100 6.3 Cost of debt...101 6.4 Conclusion Weighted average cost of capital...102 7. Valuation...102 7.1 Present value models...103 7.1.1 Discounted cash flow (DCF) model...104 7.1.2 Economic value added model...105 7.2 Relative valuation multiples...105 7.2.1 Choice of multiples...106 7.2.2 Multiple valuation...107 7.4 Sensitivity analysis...107 7.5 Scenario analysis...110 7.5.1 Scenario 1 strengthen focus on product innovation and VAP...110 7.5.2 Scenario 2 100% focus on cost efficiency...112 7.5.3 Scenario 3 Changes in fundamental input factors...113 7.6 Summary valuation...115 8. Discussion...116 9. Conclusion...117 10. Thesis in perspective...119 11. References...120 12. Appendix...126 4

1. Introduction and motivation The subject for our thesis is a valuation of the Norwegian Seafood company Lerøy Seafood Group (hereafter LSG). Our motivation fell on LSG for a number of reasons. The harvest quantity of Atlantic salmon has tripled since 1998 due to technological innovations, 1 but there is still substantial potential for growth in the industry. 70% of the earth s surface is covered with water, but only 6.5% of the per capita human protein consumption originates from water. Compared to wild fishing which is in stagnation, and land based protein production which has scarce resources, the aquaculture is estimated to increase its market share and position as a protein producer in the future. 2 A key question is thus: how can production at sea be expanded? The industry is dominated by a few countries across the world because of biological constraints, e.g. optimal seawater temperature and sheltered coastline. These countries are already pushing the limits when it comes to local capacity, environmental restraints and political restrictions. This has led the Norwegian government to put forward a new sustainable growth -legislation that will allow companies in Norway to increase their maximum allowed biomass (MAB) 3 in the future, dependent on environmental conditions. The industry is highly cyclical and dependent on one key driver: salmon price - which has fluctuated between 19- and 52 NOK per kg the last ten years. 4 The last two years have however been different than the historical cycle within the industry, with abnormal high salmon prices due to significant overperformance of demand compared to supply. It is thus interesting to see if this is a trend that will continue or if the industry will revert back to its normal pattern, and how it affects the value of LSG. LSG is the world s second largest producer of salmon and trout, and was in 2002 listed on the Oslo Stock Exchange. Since then, LSG has grown significantly due to new acquired licenses and Mergers & Acquisitions (M&A). In addition to growth, M&A activities have enabled LSG to fully integrate their value chain through horizontal- and vertical integrations. This together with R&D has given LSG a lot of media attention for innovative thinking and they received the Norwegian export prize in 2015 which makes for an interesting strategic start point - why are they successful in this area? At the same time, their stock is trading close to an all-time high and thus analyzing whether this is justified or not, is something that attracts us. In addition, the allowed ownership capacity in Norway was increased 1 Marine Harvest Handbook (2014) pg. 17 2 Marine Harvest Handbook (2014) pg. 6 & 11 3 Maximum allowed biomass - Tons biomass which the farmer is allowed to have in the sea per license at a specific time 4 www.fishpool.eu 5

from 25% to 40% in 2013 allowing large companies like LSG to become even larger. This has led, and will lead to further development of the industry, making it a very interesting one to analyze. 1.1 Problem statement Our ultimate goal is to assess LSG s performance and value through a fundamental analysis, and by applying different valuation techniques. This will enable us to give an investor recommendation of buy if our analyses show that the company is currently undervalued, hold if it shows it is fairly valued, or sell if our analysis show that the company is currently overvalued. This has led us to the following problem statement: What is the fundamental value of LSG s equity, and what is the fair price of one LSG share as of 17.04.2015, compared to the market capitalization on Oslo stock exchange? To answer this problem statement we will perform a thorough fundamental analysis of LSG, the fish farming industry and the market conditions. 1.1.1 Sub questions The thesis will be divided into different sections. In each section we will pose sub questions that will be answered through different analyses. Our findings will be summarized in partial conclusions, which we will use in our final conclusion at the end of our thesis. Below you will find an overview of all the sections, and sub questions posed in each of them. LSG and the fish farming industry In order to perform a good valuation it is essential that we get a proper understanding of the company and the industry it operates within. Insight gained in this section will lay the foundation for the strategic and financial analysis later in the thesis. Question posed and answered in this subsection will be: - What characterizes LSG and its strategy, and how has the company developed over time? - What characterizes the industry, and how has it developed over time? - What does the value chain look like, and how has the profitability in the industry developed over time? - Who are LSG s main competitors and peers? 6

Financial analysis In the financial analysis our goal is to uncover historical operating performance through analysis of key ratios and value drivers. The historical performance will be a good indicator for future growth, profitability and risk. Together with the strategic analysis it will lay the foundation for our forecasted income and balance sheet later in the thesis. Questions posed and answered in this section will be: - How has LSG s profitability developed over time, and compared to peers? - What are the key drivers behind value creation for their owners? - How is LSG s liquidity and financial position? Are they able to undertake profitable investments in the future? Strategic analysis In the strategic analysis we will analyze non-financial factors that influence the profitability of LSG and the industry. First we will analyze the internal drivers and how LSG s strategy influences their profitability through a VRIO analysis. We will then look at external factors that influence LSG s and the industry s profitability potential in the future. Questions posed and answered in this section will be: - What are LSG s strategic strengths and weaknesses? - What shapes industry competition, and how intense is it? - How do external factors affect the industry and the profitability? - How is the salmon price determined? Forecasting In the forecasting section of the thesis we will use our findings from the financial and strategic analyses to make a pro forma statement for LSG. - How will our estimates influence LSG s income statement and balance sheet? - Are our estimates realistic? - What is the proper discount rate for an investor in LSG? 7

Valuation In the last section of our thesis we will derive LSG s enterprise and equity value using the inputs from our pro forma statements. In order to triangular and validate our findings we will benchmark our results against a relative valuation. Further, we will look at how sensitive our model is to changes in key input factors, and compare our results to those of investment banking professionals. Questions posed and answered in this section will be: - What is the fundamental value of one LSG stock? - What is the relative value of one LSG stock? - How sensitive is our valuation to changes in key factors? - What happens to the stock price if LSG s strategy fails/changes? 1.2 Methodology and structure In this section we will briefly describe the methods used for data collection, theories and the structure of the thesis. The purpose is to give the reader an overview of the design and methods used in the thesis. 1.2.1 Data collection This thesis is written from the perspective of an individual investor/analyst, and as such only publicly available data and information has been used. Most of the data has been collected from annual reports, quarterly reports, industry reports, news articles and stock exchanges. We have also found sources that have deep insight into the industry, through researching the web for articles, lectures etc. All data collected and used in the thesis will be referenced in footnotes and in the reference list at the end of the thesis. 1.2.2 Theories In order to be as theoretical correct as possible, we have used a wide range of theoretical sources in all parts of our thesis. We feel that using multiple sources of theoretical framework put us in a good position to evaluate which theories and models to follow, and different viewpoints made us recognize that there are different ways of solving the task at hand. We feel that a short introduction of theories used is best placed at the beginning of each section, to give a better overview for the reader. 8

1.2.3 Structure The thesis will be structured into multiple sections in order to give the reader a good overview throughout the text. Each section has been carefully selected to answer key questions that will put us in a good position to answer the main problem statement above. The structure of the thesis is shown in the figure below: Figure 1.1: structure of thesis Source: Authors creation 9

1.3 Delimitations Due to factors such as time, data availability, and space limitation, some delimitations are necessary. This will also contribute to make our thesis focused on solving the main problem statement and sub questions. The following limitations have been made: - As we take the stance as an outsider giving advice to potential investors and to deter biasness, we will base our analysis solely on publicly available information like annual reports, quarterly reports, articles, newspapers, industry reports etc. - We expect the readers to have general knowledge about financial, economic and strategic theory, and will thus not explain each model in detail. - The cut-off date for our valuation is the 17 th of April 2015, thus information dated later than this will not be used in this thesis. We have used a period of 10 years to analyze historical data. - The sole focus of this thesis will be on Atlantic salmon, even though LSG produce and sell other species. This is because other species historically have accounted for a small percentage of overall sales and performance, and due to time and space limitations, as well as limited information on other products in annual reports. - The salmon price used in this thesis is collected from fishpool.eu, and the Norwegian spot price is treated as a universal price throughout the thesis. - We will not explicitly model forward sales contracts. - We will not explicitly model potential mergers and acquisitions, but will assume such activities will contribute to growth in licenses and harvest volumes in the future. - A constant WACC is assumed in our valuation model. 10

2. LSG and the fish farming industry In this section we will give an introduction to LSG and the fish farming industry. It is essential that we understand the mechanisms within the company and the industry if we want to perform a good valuation. Furthermore, it gives the reader an understanding of the industry and what drives profitability and growth. 2.1 LSG LSG is the world s second largest producer of Atlantic salmon and trout, and a leading Norwegian exporter of seafood. 5 The company dates back to the 19 th century and the fishing docks in Bergen, where Ole Mikkel Lerøen started selling live fish. In 1939, Hallvard Lerøy Sr. and Elias Fjeldstad established Hallvard Lerøy AS a company which remains the group s principal sales company today. 6 LSG has since the start strived to be a pioneer and develop new markets for seafood, which has led to them becoming an industry leader within innovation. LSG was family owned until 1997, when they carried out their first private placing with financial investors and became a public limited company. They were listed on Oslo Børs in June 2002 in order to fund their development from a seafood exporter to a fully integrated seafood group. 7 Over the last fifteen years, LSG has experienced significant growth based on well-developed operations, acquisitions, development of acquired companies and by building worldwide alliances. 8 From 2004 to 2013 the company experienced an average growth rate of 15%, and their aim for the future is to sustain this growth rate over the coming years. 9 Today the company has a market capitalization of 12.83 billion NOK and supply the equivalent of three million meals of seafood to over 70 markets worldwide on a daily basis. 10 In 2014 they exported more than 220 000 tonnes of seafood, and their product portfolio includes more than 2500 products. Today, LSG s core activities are distribution, sales and marketing of seafood, processing of seafood, production of salmon, fjordtrout and other species, as well as product development. Their operations have a global reach, with sales offices spread across the world and more than 2300 employees. 5 Lerøy Seafood - Annual Report (2014) pg. 11 6 https://www.leroyseafood.com/en/business/about-us/history1/ 7 https://www.leroyseafood.com/en/business/about-us/history1/ 8 Lerøy Seafood - Annual Report (2014) pg. 11 9 Lerøy Seafood - Annual Report (2013) pg. 9 10 https://www.leroyseafood.com/en/business/about-us/leroy-in-brief/ 11

2.2 The salmon farming industry The ultimate goal for the coming sections is to give an in-depth introduction to the salmon farming industry and key profitability drivers. This will prepare the reader for the coming analysis of LSG and the industry. Salmon farming is a subgroup of the aquaculture industry which is defined as the production of aquatic organisms such as fresh- and saltwater fish, molluscs, crustaceans, plants etc. under controlled conditions, 11 as opposed to commercial harvesting of wild fish. Wild capture of fish has been in stagnation in recent years and future growth in supply is expected to come from the aquaculture industry, 12 which is the fastest growing animal-based food producing sector, providing 47% of all fish supplies destined for human consumption in 2013. Salmon is the common name for several species of fish of the family Salmonidae, e.g. Atlantic salmon, Pacific salmon and trout. Salmons are anadromous, meaning that they are born in fresh water and then migrates to the ocean, and today 60% of the world s salmon consumption originates from fish-farming facilities. In this thesis we will focus on LSG s main product: Atlantic salmon. The Atlantic salmon farming industry, as we know it today, started in Norway in the early 1970 s when the production was moved from land based plants to floating cages at sea. This resulted in better growing conditions, lower costs and less risk for participants. 13 Today, almost all commercially available Atlantic salmon is farmed and 2 million live weight tonnes was harvested globally in 2012. Although production has increased with almost 600% from 1990, total global supply of salmonids only represents 4.2% of the global seafood supply. 14 2.2.1 Historical development of global supply (production regions) Norway is by far the dominant producer with 54% of total global salmon supply. The second largest producer is Chile, and together they represent 80% of the total supply. Production of salmon only takes place in a few big regions, and total supply by region can be found in table 2.1. 11 http://www.fao.org/fishery/statistics/global-aquaculture-production/en 12 Marine Harvest Handbook (2014) pg. 5 & 7 13 Universitet i Bergen, Band 5 Havruk «Havbruksnæringen et eventyr i Kyst-Norge» 14 MHG handbook, 2014, page 9 12

Table 2.1: Harvest volume per region. Region ( 1000 tones) Harvest Volumes 2014E CAGR 1994-2014 Norway 1198 9 % Chile 583 14 % UK 174 5 % Canada 101 6 % Faroe Island 82 5 % Other 99 7 % Total 2237 9 % Source: Compiled by authors', Nordea markets seafood sector update 25.03.2015 The reason why production is dominated by a few countries is biological constraints as seawater temperature and sheltered coast line, which are requirements for optimal production. 15 Chile has since the start of the century aggressively increased their production of salmon. As a result of their aggressive increase, they met a serious setback in 2009 when the infectious salmon anemia (ISA) virus plagued the region. The virus decreased the production with 50% from 2009 to 2010, resulting in high salmon prices. 16 A clearer picture of the annual growth in harvest volume and the decrease due to the ISA virus can be seen in appendix 2.1. Chile has since rebuilt its production, while the production in UK and North America has been steady in recent years with limited growth potential. 17 2.2.2 Markets Figure 2.1: Overview salmon markets and supply flow Source: MHG Handbook 2014 15 Marine Harvest Handbook (2014) pg. 12 16 The average yearly price rose from 25.8 in 2007 to 37.3 in 2010, as seen in appendix 5.2 17 Marine Harvest Handbook (2014) pg. 17 13

As seen in figure 2.1, the largest markets for head-on-gutted (hereafter HOG) Atlantic salmon are Europe (incl. Russia) and North America, while South America and Asia are examples of smaller markets that are developing at a rapid pace. Each of the production regions have historically focused on developing nearby markets as most salmon is sold as fresh product and it is costly and time consuming to transport it to other parts of the world. 18 Main markets for each production origin have historically been: - Norway: EU, Russia and Asia - Chile: USA, South America and Asia - Canada: Western part of USA - Scotland: Domestic / within the UK ( Limited export) For fresh salmon, a relative high price differential is required in order to justify trades across the Atlantic as it requires cost of airfreight. However, it is expected that the market for fresh salmon will continue to grow and the limited supply from Chile between 2009 and 2010, gave European producers a chance to establish themselves in the North-American market. 19 In addition, the weak Norwegian currency has made Norwegian salmon an attractive option for the North-American market. 20 2.2.3 MAB, market concentration and licenses Since 1973 it has been regulated by law that you need a license in order to operate a salmon farm in Norway. One license allows a maximum allowed biomass (hereafter MAB) of 780 tons in central, western and southern Norway, while sites located in Troms and Finnmark are allowed to produce 945 tons due to lower water temperature which decreases the risk for disease outbreaks. 21 The license regulation restricts the harvest volume for companies and the industry as whole, forcing companies to focus on capacity utilization and M&A in order to grow. The annual harvested quantity in Norway is around 1200 tons HOG per license. 22 Larger companies like LSG and its peer group have technology that enables them to maximize the output per licenses, which widens the gap between the big and small companies in the industry. The Norwegian Directorate of Fisheries normally offers licenses to smaller players in the industry to encourage value creation in rural areas. At the same time, they allowed for a greater degree of ownership concentration from the early 90 s, which started a M&A weave within the industry. The last decades have thus been through a period of concentration, not only in Norway but in all fish-farming regions around the 18 Marine Harvest Handbook (2014) pg. 20 19 Marine Harvest Handbook (2014) pg. 20 20 Will be discussed further in the strategic section 21 Lovdata (24.06.2013) Forskrift om tildeling av løyve til havrk med matfisk av laks 22 Marine Harvest Handbook (2014) pg. 53 14

globe. 23 Furthermore, the government increased the maximum allowed ownership of licenses from 25% to 40% in 2013, and the concentration trend is thus expected to continue over the next decade. 24 M&A is mainly conducted in order to gain advantages through economics of scale, but it also gives access to new financing sources. 25 As a result of this, there has been an inflow of fish farming companies on Oslo Stock Exchange in recent history. Graph 2.1: License development from 1992-2014, Norway Source: Authors creation, Directorate of Fisheries There has been slow growth in licenses since 1994, and only a limited number of licenses have been awarded since 1982. 26 In 2009, there were allocated 65 new licenses in Norway, and by 2014 48% of these were resold to a company that is owned wholly or partly by one of the major aquaculture operators in Norway. 27 These licenses were heavily discounted and only sold for 8 MNOK to small companies. 28 At the end of 2014, there were a total of 973 licenses in circulation in Norway. 2.2.4 Production of salmon After receiving a license, it has to be utilized within two years with a minimum of one third of the allowed biomass. 29 In order to equip a fully grown-out facility in Norway, a total of 850 000 smolt must be released. This requires an estimated 25-30 million NOK investment in cages, feed barge/automats, nets, mooring, cameras and boats. 30 The production cycle for Atlantic salmon is approximately 24-38 months, where 10-16 23 Marine Harvest Handbook (2014) pg. 28 24 FondsFinans - Aquaculture Sector Report (10.04.2015) pg. 30 25 O. Kvaløy & R. Tveterås (Økonomisk forum nummer 5. 2006) Den integrerte oppdrætsnæringen pg. 4 26 Marine Harvest Handbook (2014) pg. 51 27 Verdens Gang (VG) (16.01.2014) «Her har de store lakseoppdretterne slukt de små» 28 Normal price is in the range of 40-60 MNOK 29 Marine Harvest Handbook (2013) pg. 29 30 Marine Harvest Handbook (2014) pg. 47 15

months are in freshwater and 14-22 months are in seawater. The whole production cycle can be seen in appendix 2.2 First the eggs need to be fertilized, and then the next 10-16 months takes place in closed tanks on land with controlled freshwater environment. The reason for using fresh water is that it contains more oxygen and has better light conditions which are essential in this part of the growing phase. 31 When the fish becomes 100 grams (so called Smolt) they are transferred to sea cages in quiet water located in fjords or bays. At this stage, salt water and sea temperature will enable the salmon to grow optimally. After 14-22 months in seawater the salmon should reach a harvestable size, normally 4 to 5 kg, which varies between regions and the time of year. 32 When the salmon have reached its harvestable size, they are transported to harvesting plants in wellboats where they are slaughtered and gutted. This cycle is slightly shorter in Chile due to more optimal and stable seawater temperature. The salmon processing is divided into primary- and secondary processing also known as Value-added products (VAP). 33 The primary processing includes slaughtering and gutting, which make up standard price indexes for farmed salmon. Secondary processing includes portioning, filleting, making ready-to-eat meals, packaging with modified atmosphere etc., which is a significant value driver for LSG. 34 LSG and similar companies covers all the aspects of the value chain, which enables them to control their market timing and biological risk to a larger extant than smaller companies. In addition, having control of the whole value chain enables LSG to ensure a higher quality and reduces price risk throughout the value chain. 35 2.2.5 Cost structure Norway has some competitive advantages within the industry with optimal climatic conditions and a sheltered coastline. However, Norway is one of the richest countries in the world and the cost of labor is generally higher than in other countries. Norway is still the dominant country within the industry because of continuous efficiency improvements, where R&D and knowledge has been the fundamental factors for industry progression. 36 The harvest volumes have grown almost 20 times over the last 25 years, with only a slight increase of employees. 37 This is due to a production which has been automated and has become very 31 Institute of Marine Research (14.09.2009) Biologi hos laks i oppdrett 32 Marine Harvest Handbook (2014) pg. 29 33 Marine Harvest Handbook (2014) pg. 65 34 This will be discussed further in the financial and strategic analysis. 35 O. Kvaløy & R. Tveterås (Økonomisk forum nummer 5. 2006) Den integrerte oppdrætsnæringen pg. 4 36 Atle G. Guttormsen & Kenneth Løvold Rødseth The economics of Norwegian Salmon farming 37 Nordic Marine Innovation Markeds- og verdikjedeanalyse pg. 29 16

efficient. The labor productivity has however stabilized after 2005, and the efficiency improvements have not been large enough to cover increasing prices of input factors in Norway. 38 Table 2.2: Detailed cost level per region Input costs Norway (NOK) % Canada (CAD) % Scotland (GBP) % Chile (USD) % Feed 12,4 50,20 % 2,26 41,17 % 1,5 45,59 % 2,22 43,53 % Primary processing 2,52 10,20 % 0,56 10,20 % 0,25 7,60 % 0,41 8,04 % Smolt 2,31 9,35 % 0,52 9,47 % 0,31 9,42 % 0,52 10,20 % Salary 1,51 6,11 % 0,52 9,47 % 0,18 5,47 % 0,18 3,53 % Maintenance 0,82 3,32 % 0,23 4,19 % 0,08 2,43 % 0,22 4,31 % Wellboat 1,02 4,13 % 0,2 3,64 % 0,22 6,69 % 0,29 5,69 % Depreciation 0,77 3,12 % 0,21 3,83 % 0,11 3,34 % 0,15 2,94 % Sales & Marketing 0,56 2,27 % 0 0,00 % 0 0,00 % 0 0,00 % Mortality 0,15 0,61 % 0 0,00 % 0,04 1,22 % 0,11 2,16 % Other 2,64 10,69 % 0,99 18,03 % 0,6 18,24 % 1 19,61 % Total 24,7 100 % 5,49 100 % 3,29 100 % 5,1 100 % Source: Authors' creation, Marine harvest handbook 2014 All input factors related to production of salmon can be seen in the figure above. Feed is the largest cost in all regions, while primary processing and smolt are either the second or third most expensive input factor. 2.2.6 Historical profitability and the state of now An industry is characterized as cyclical when the earnings show a repeating pattern of up- and downturns. 39 The production cycle of Atlantic salmon is approx. three years, and the production level is therefore difficult and expensive to adjust in the short therm. This results in a very inelastic short term supply quantity, which has an effect on the volatility in spot- and forward price. 40 The demand for salmon is also characterized by seasonal variations. Graph 2.2: Historic price, cost and EBIT per kg Source: MHG Handbook 2014 38 Vassdal, T. Havbrukskonferanse i Oslo (22.11.2011) Produksjonskostnader for laks i Norge, Chile og Skottland 39 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 66 40 Marine Harvest Handbook (2014) pg. 24 17

The development from 1993-2013 shows a cyclical pattern in the fish farming industry, where two to three years of a downward trend is followed by a two to three years upward trend. The reason for this is that fish farmers historically have increased smolt release when the price of salmon is high and reduced it when the price is low. The increased smolt release will reach the market within 12-18 months, which increases the quantity of supply and reduce the prices. In response to a lower price, fish farmers have reduced smolt release, which has been followed by an increase in profitability. Share prices of fish farming companies have also followed this cycle, a trend analysts and investors has become more aware of. Table 2.3 shows a generally high correlation between the stock prices of the peer group 41 and salmon price from Fish Pool Index in the period 1 st January 2009 to 17 th of April 2015. Table 2.3: Correlation between stock prices and salmon price Correlation with FPI Lerøy SALM MHV GSF Weekly 0,59 0,52 0,66 0,72 Source: Compiled by Authors', yahoo finance, fishpool The high correlation and cyclical nature in the industry is something we will keep in mind when analyzing LSG and its peers later in this thesis. It is also worth noting that the cyclicality of the salmon price has changed in recent years, and was stable from 2013 to 2014. This is a development that is expected to continue into the future, as the industry has gone through a rapid growth phase, and now enters into a maturing phase. This phase is characterized by more stability and foresight, and makes the future easier to predict. 42 2.3 Historical events and share price development, LSG Graph 2.3: Share price development and important historical events Source: Authors creation, Yahoo finance, annual reports, leroyseafood.com 41 Will be defined below 42 Pareto Equity research rapport (10.04.2015), pg. 3 18

Graph 2.3 illustrates the share price of LSG and important historical events. LSG was listed on the Oslo Stock Exchange 03.07.2002 with a share price of 17 NOK. This was done in order to improve future access to risk capital and improved opportunities for using the company s shares in future acquisitions and mergers. 43 Since then, the company has grown rapidly, expanding its harvest volume and value chain both organically and through M&A. A more detailed description of historical events can be found in appendix 2.3 The development of LSG s share price has since the IPO been volatile with up- and downward trends. Acquisitions and investments has been important in order to transform the company into a fully integrated seafood company, increase value creation and thus share price. The sharp decrease in 2011 was a result of low production volumes, a low salmon price, and consequently worse expectation for the future. The opposite occurred when the share price increased from 2012 to 2015. The share price reached its highest share price of 283 NOK the 19 th of January 2015. Today, the share price is traded at 235, providing a compounded annual return of 18.3% since the IPO. 44 2.4 Business concept and strategy LSG s strategy is to meet demand for seafood and culinary highlights, both at home and abroad, by supplying high quality products. 45 Furthermore, LSG strive to develop profitable, efficient and binding partnerships through their high quality seafood products. Historically the company has always had a focus on delivering high quality and fresh produce to its customers around the world. Over the last years, the company has also focused heavily on sustainable production, and in line with their new focus their vision changed from LSG s vision is to be the leading and most profitable global supplier of quality seafood to LSG s vision is to be the leading and most profitable global supplier of sustainable seafood. 46 As a result of their changed focus, LSG was the first company to be awarded ASC-certification by WWF in 2013. 47 The same year the company entered into cooperation with Bellona 48 to found ocean forest A company focusing on R&D based on integrated multi-trophic aquaculture. 49 Furthermore, a central part of the group s strategy is to maintain a strong focus on the market and everchanging demand for differentiated products. To meet future demands the group actively develops new 43 Lerøy Seafood - Annual Report (2002) pg. 14 44 CAGR = (IPO price (17) / Price Today (235) ) ^( 1 / Years (13) ) - 1 45 https://www.leroyseafood.com/en/investor/about-leroy/business-concept-and-strategy/ 46 Lerøy Seafood - Annual Report (2014) pg. 11 47 https://www.leroyseafood.com/en/business/products/quality/certifications/asc/ 48 A Norwegian non-profit organization that aims to meet and fight climate challenges 49 Lerøy Seafood - Annual Report (2013) pg. 11 19

markets and new products from fisheries and aquaculture based on sustainable principles, with the aim to develop profitable, efficient and binding alliances both nationally and internationally for both supply and marketing. 50 New products and markets require knowledge and proximity to both consumer and markets, and in line with this strategic goal, LSG has opened several new VAP plants across Europe in recent years. 51 2.5 Value chain A firm s value chain is a reflection of its history, its strategy, implementation of strategy, and the underlying economics of the activities itself. 52 Analyzing the value chain of a company is key to understanding where the firm creates value for its consumers and thus eventually stakeholders. The value chain will here be defined as the value creating activities all the way from basic raw material sources from component suppliers through to the ultimate end-user product delivered into the consumers hands. In the case of LSG, this is the entire lifespan of salmon through the production of finished goods and distribution, and until the product reaches the consumer. LSG s Value chain can be found below: Figure 2.2: LSG s Value chain LSG have a fully integrated value chain, and play an active role in all parts of the value chain for production of salmon. Eggs LSG produce all their eggs on their own, and have a production capacity of over 100 million fertilized eggs per year. 53 Smolt production LSG follows a principle strategy to remain self-sufficient when it comes to quality smolt, and are thus not reliant on suppliers in this stage of the value chain. In 2014 they had a production capacity in excess of 57 50 Lerøy Seafood - Annual Report (2014) pg. 11 51 Lerøy Seafood - Annual Report (2014) pg. 18 52 Institute of Management Accountants (1996) Value Chain Analysis For Assessing Competitive Advantage. pg. 1 53 http://miljorapport.leroy.no/en/leroy-seafood-group/verdikjeden-i-havbruksvirksomheten/ 20

million smolt. 54 Further the group have invested heavily on onshore smolt production facilities in order to ensure the best quality possible, and to make sure that smolt are not transported over larger distances before they are ready to leave the smolt facilities and go into the farming facilities at sea. They have also invested in facilities that will enable them to grow larger smolt, and have procedures in place that ensures that the smolt comes from the highest quality fish, which are selected based on genetic markers for extra resistance to infectious pancreatic necrosis and other diseases. 55 Farming and fish feed After the fish has developed in the fresh water facilities onshore, they are transported to fish farming cages at sea. While at sea, one of the most important input factors is fish feed. Quality assurance of feed and feed raw material is thus absolutely essential for the firm. In this step of the chain LSG is dependent on key suppliers, and they have a close working partnership with two of the biggest global feed suppliers, EWOS and Skretting. 56 Through their close working relationship with key feed suppliers, they ensure quality control over their fish feed through audits of these firms and their suppliers. In recent years, there has been a change in the way fish feed is composed as a result of supply of raw materials and an increased focus on sustainable production. 57 The combination has gone from 70% content of marine raw material to 70% vegetable raw materials, in line with LSG s sustainable strategy and vision. Harvesting, production and Value-adding processing (VAP) Once the fish have reached an acceptable weight, they are harvested and sent for processing. LSG sells around 50% of its salmon as whole salmon, the rest is sent to their VAP factories, to make ready to sell products. LSG made substantial investments in their VAP segment in Norway, Sweden and the Netherlands during 2013, which resulted in a profit growth of 28% in 2014. 58 This will be discussed further in the next section. Sales and distribution The sales and distribution segment has a global reach and is comprised of sales, marketing, product development, distribution and simple processing of both LSG s own products as well as for external suppliers. Over 80% of LSG s distributed products are fresh produce, which place extremely high requirement on market proximity and efficient logistics. 59 LSG have thus made significant investments in this area in recent years. This point will be discussed closer in the next section. 54 Lerøy Seafood - Annual Report (2014) pg. 8 55 http://miljorapport.leroy.no/en/leroy-seafood-group/verdikjeden-i-havbruksvirksomheten/ 56 Lerøy Seafood - Annual Report (2014) pg. 44 57 Lerøy Seafood - Annual Report (2014) pg. 45 58 Lerøy Seafood - Annual Report (2014) pg. 9 59 Lerøy Seafood - Annual Report (2014) pg. 18 21

2.6 Corporate structure Figure 2.3: LSG s Corporate structure Lerøy Seafood Group ASA Farming/production VAP Sales & distribution Source: Authors creation, LSG annual report 2014 LSG divide their operations into three segments: Farming/production, VAP, and sales and distribution. Their operations are viewed as regional with a global perspective. 60 Figure 2.4: Harvest volume per region, LSG Comapny Region Licenses Leøy Aurora AS* North 26 20 000 24 200 26 800 Lerøy Midt AS Mid 55 61 900 58 900 68 300 Lerøy Sjøtroll West 60 71 600 61 700 63 200 Total Norway (consolidated) 141 153 500 144 800 158 300 Villa Organic AS** 6 000 Norskott Havbruk (UK) 13 600 13 400 13 800 Total 167 100 158 200 178 100 * Villa Organic consolidated as of 01.07.2014 ** LSG's share of Villa organic 's volume H14, not consolidated Consolidated farming Not consolidated farming 2012 GWT Source: Authors creation, LSG annual report 2014 Farming/production 2013 GWT 2014 GWT Figure 2.5: Geographical location farming Source: LSG annual report 2014 Farming/production activities are divided in by region: Lerøy Sjøtroll is their farming company in Western Norway, Lerøy Midt AS in Central Norway, and Lerøy Aurora AS is their farming company in Northern Norway. Northern Norway Lerøy is present in Northern Norway through their fully integrated producer of salmon: Lerøy Aurora AS. In 2013 LSG bought a 49.5% stake in Villa Organic and the company was fully consolidated into Lerøy Aurora 60 Lerøy Seafood - Annual Report (2014) pg. 12 22

AS and LSG 01.07.2014. With this consolidation, the region gained 8 new licenses for production in Northern Norway, and they now operate a total of 26 licenses in the region. 61 The new acquisition will give room for further growth in the area. Lerøy Aurora is currently the groups smallest and most profitable farming/production company with an EBIT/KG of 13.8 in 2014. 62 Central Norway LSG is present in Central Norway through their 100% stake in Lerøy Midt AS. LSG controls a total of 55 licenses, and with a harvest volume of 68 300 GWT in 2014 it was the groups largest producer of Atlantic salmon. The region experienced an increase in biological challenges in 2014, through more problems with sea lice and the first ever occurrence of amoebic gill disease (AGD). 63 Despite these problems, the region reported an EBIT/KG of 9.8 in 2014. 64 The group has made several investments in new smolt facilities in the region in order to streamline production, and improve the biological conditions in the future. 65 Western Norway LSG is represented in Western Norway through Lerøy Vest AS, which is a fully integrated subsidiary and Sjøtroll Havbruk AS, of which the group owns 50.71%. In total they operate 60 licenses in the region, and it was the second largest operation with a harvested volume of 63 200 GWT in 2014. It is also the only region in which LSG farm Atlantic trout in addition to Atlantic salmon. The region is currently the least profitable with an EBIT/KG of 4.5 in 2014, with trout production having a large negative effect. 66 Western Norway is a very challenging region to run operations. Because of higher sea water temperature the instances of sea lice have been an especially challenging area for Lerøy Vest AS. As a result, the group has made large investments in cleaner fish in this region, and expects treatment costs to fall significantly in the future. 67 Value added processing (VAP) As part of their strategy, LSG has and will continue to invest considerable amounts of money in the processing of Atlantic salmon and trout. 68 With their VAP segment, they supply a wide variety of products 61 Lerøy Seafood - Annual Report (2014) pg. 15 62 Lerøy Seafood - (Q4 Report) pg. 24 63 Lerøy Seafood - Annual Report (2014) pg. 16 64 Lerøy Seafood - (Q4 Report) pg. 25 65 Lerøy Seafood - Annual Report (2014) pg. 16 66 Lerøy Seafood - (Q4 Report) pg. 26 67 Lerøy Seafood - Annual Report (2014) pg. 16 & 37 68 Lerøy Seafood - Annual Report (2014) pg. 17 23

such as portion sizes, smoked and cured salmon, sandwich fillings and ready-to-cook products. Their VAP operations are largely ran through the following companies: - Lerøy Fossen AS - a processing company for salmon and trout which has the largest smoking facility in Norway - Lerøy Smøgen seafood AB - A Swedish seafood company involved in producing a variety of smoked and ready-to-eat products. The company also has one of the world s most modern and efficient facilities for production of highly processed salmon. - Rode Beheer - A Dutch Company, which is a leading producer of processed seafood with an important strategic location close to the Benelux countries, Germany and France. Sales and distribution Figure 2.6: Geographical location S&D Source: LSG annual report 2014 A central aspect of LSG s growth strategy is to offer new products to new markets, and today they sell their products to more than 70 different markets. 69 In order to do so, knowledge of and proximity to customer and market is key. In order to reach these markets, LSG have sales offices in a number of countries, including China, Japan, and North America. In recent years, they have also opened up several fish-cuts around Europe. These are factories/facilities in the end market with relatively simple processing, large 69 Lerøy Seafood - Annual Report (2014) pg. 17 24

volumes, and where proximity to the consumer is key. 70 The group hopes that these new facilities will be a revolution within distribution of fresh fish. Their main sales and distribution company is Hallvard Lerøy AS, and it has the highest turnover of all the group companies. In 2014 the company reached a turnover above 10 bn. NOK for the first time ever. Hallvard Lerøy focuses on customer needs and cost efficient handling of individual clients, and the company s presence around the world is seen as a competitive advantage as it allows for close follow up of key customers and establishing new customer relationships. 71 Furthermore, LSG opened Europe s largest and most innovative facility in corporation with their strategic partner in the Norwegian market, Norgesgruppen, in 2014. 72 Sjømathuset has a capacity of 8-10 000 tonnes and 20 million pieces of sushi per year, and has opened the door for a revolution in the distribution of freshly packaged fish and sushi in Norway. With an estimated turnover of 450 million during the first 8 months of operations, LSG has high hopes for Sjømathuset and the Norwegian market going forward. 2.7 Group management and key board directors CEO Henning Beltestad 73 Henning Beltestad was officially appointed CEO at LSG in April 2010, but was interim CEO from December 2009. He has had various roles within the company since 1993, and was CEO of Hallvard Lerøy from 2007 until he took over the role as interim CEO. He owns no shares in LSG. Executive vice president, farming Stig Nilsen Stig Nilsen has been employed with LSG since 2003, when he became the CEO of Lerøy Aurora AS. He has extensive experience from the fish feed industry and fish-farming industry, and is thus a valuable asset when it comes to farming activities. He owns 1 784 shares in LSG. CFO Sjur Malm Sjur Malm was appointed CFO of LSG the 1 st of October 2012. He has previously worked as an analyst for SEB, where he was responsible for the fishing and industry sector. He has several times been named the best analyst in Norway within the fish-farming sector. He owns 1 500 shares in LSG. Chairman Helge Singelstad Helge Singelstad is a previous CEO, vice CEO and CFO of LSG and thus have broad knowledge of the group and the fish farming industry. He is currently chairman of Austevoll Seafood ASA, member of the board of 70 Lerøy Seafood - Annual Report (2014) pg. 18 71 Lerøy Seafood - Annual Report (2014) pg. 18 72 https://www.leroyseafood.com/en/business/about-us/news/2014/sjomathuset/ 73 https://www.leroyseafood.com/en/investor/about-leroy/group-management/ 25

DOF ASA, and managing director of Laco AS. He owns LSG shares indirectly through shareholdings in Austevoll seafood ASA. Board member Arne Møgster Arne Møgster has been on the board since May 2009. Mr. Møgster is the CEO of Austevoll seafood ASA, one of the main owners of LACO AS 74 and a board member in a number of other companies. Mr. Møgster thus has extensive experience within the seafood industry. Mr. Møgster owns LSG shares indirectly through Laco AS and Austevoll seafood ASA. 2.8 Ownership Table 2.4: Ownership structure as of 31.12.2014 Ownership, 31.12.2014 No of shares Ownership Austevoll Seafood ASA 34 144 281 62,6 % Folketrygdfondet 2 278 041 4,2 % Pareto Aksje Norge 1 604 297 2,9 % State streetbank & trust co. Om80 773 664 1,4 % Pareto Aktiv 676 060 1,2 % Total 5 largest 39 476 343 72,3 % Other 15 101 025 27,7 % Total share capital 54 577 368 100,0 % Source: Compiled by authors', Lerøy seafood annual report 2014 The ownership of LSG is listed above. Austevoll seafood ASA is the majority shareholder with 62.6% ownership, while all other shareholders are minority owners. Austevoll seafood ASA is a Norwegian company listed on Oslo Børs, and is controlled by Arne Møgster and his family through Laco AS. This means that the ownership structure is highly focused, and the company is controlled by people that have extensive experience within fish-farming industry. Despite the ownership being focused, we deem it as positive for the company and its minority shareholders, as the people controlling LSG have extensive experience and there seems to be financial alignment among key decision makers. 74 Laco AS is a Norwegian holding company that owns 55% of Austevoll seafood ASA 26

2.9 Financial performance and development Graph 2.4: Historical performance LSG Source: Authors creation/lsg ARs 2005-2015 LSG has experienced rapid growth since 2005, both organically and through mergers and acquisitions. Their harvest volumes have grown from 52 000 in 2005 to 168 300 tonnes in 2014, this corresponds to a CAGR of 13.2%. As a result revenues have had a positive development with a CAGR of 13.5%, and NOPAT has grown with a CAGR of 20.4%, despite being highly volatile. This is because NOPAT is heavily dependent on the underlying salmon price. To illustrate this picture we have plotted return on invested capital against salmon price in the figure below: Graph 2.5: ROIC VS Avg. Salmon price Source: Authors creation/lsg ARs 2005-2015 27

2.10 Introduction to peer group The purpose of defining a peer group is to analyze LSG s relative performance over an historical period. The peer group will be used as a benchmark in the financial- and strategic analysis, in addition to the relative valuation using multiples. There are a few considerations that must be taken into account before defining a peer group. A peer group does not necessarily need to consist of competitors, but it is important that the firms are comparable in terms of business characteristics and operations. The financial statements must also be based upon the same accounting principles. 75 The risk profile among the companies in the peer group should also be alike, and the peers should have the same outlook for return on capital (ROIC) and long term growth when using multiples. 76 Figure 2.7: Peer group selection Source: Authors creation/nordea Markets As previously described, the salmon industry is a segment with a few large companies and several small actors. The figure above lists seven Norwegian farming companies listed on Oslo Stock Exchange combined with their respective value chain. In order to determine a relevant peer group for LSG, we have looked at the value chain, homogeneity and similarities in operations, similarity in size, regional presence, structure, significant historical data availability and maturity. Based on this, our peer group consists of three companies: Marine Harvest Group (MHG), SalMar (SALM) and Grieg Seafood (GSF). 75 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 65 76 Koller,T. Goedhart,M. and Wessels,D. (2010) Valuation pg. 305 28

Cermaq has historically been one of the largest companies within the fish industry, but they have a major share of their operation within fish feed, making financial comparison less relevant. Even though Cermaq sold their feed division, EWOS, which represented around 70% of their revenue in 2013, they only have one year of relevant comparison which makes us exclude Cermaq from the peer group. 77 Norway Royal Salmon (NRS) is excluded due to large part of revenue related to buying and selling salmon in addition to limited VAP- and smolt activity. Bakkafrost is excluded because 36% of their operating revenues was related to fishmeal, oil and feed in 2014. 78 differences in size, business characteristics and lack of information. Other seafood companies have been excluded as a result of large As in every industry, there will always be deviations among the peers, which is important to pay attention to during further analysis and valuation. LSG and MHG are more weighted in VAP and other fish farming species compared to GSF and SALM. In addition, MHG and GSF are more globally diversified compared to LSG and SALM which are more weighted in Norwegian production. This can indicate different risk and income base, but large correlation across regions and converging production costs will reduce this problem of comparison between companies. 79 The chosen companies are among the top five largest producers of Atlantic salmon in Norway. 80 The table below gives an introduction of the peer group based on numbers from their annual reports and stock price per 17/4. Table 2.5: Key figures LSG and peer group Company Harvest Market Cap. Revenues EBITDA-margin Volume, tonnes NOK bn. 17/4 NOK bn. NOK per KG Lerøy Seafood 158 300 12,8 12,6 12,9 Marine Harvest 418 873 42,7 25,3 11,8 SalMar 141 000 13,4 7,2 15,1 Grieg Seafood 64 736 3,0 2,7 6,1 Source: Compiled by authors'. Yahoo finance, annual reports Marine Harvest Group (MHG) MHG is the largest producer of Atlantic salmon in the world with about 17% of the total production. The company is represented in 23 countries, but its farming- and processing activities are mainly located along the Norwegian coastline (207 licenses), Chile, Scotland, Ireland, Canada and Faroe Islands. Its business covers all the aspects of the value chain and they produce 6 million meals every day. In addition to fresh 77 www.cermaq.com History 78 Bakkafrost - Annual Report (2014) pg. 83 79 Vassdal, T. Havbrukskonferanse i Oslo (22.11.2011) Produksjonskostnader for laks i Norge, Chile og Skottland 80 Marine Harvest Handbook (2014) pg. 27 29

and frozen salmon, MHG offers a wide range of products as well as halibut farming. MHG is listed on Oslo Stock Exchange and New York Stock Exchange and has 11 715 employees. 81 SalMar (SALM) SALM is the third largest salmon company in Norway and the world, and is recognized as the most costefficient producer of farmed salmon. The company is vertically integrated through their value chain from smolt to harvesting, processing and sales. SALM owns 100 licenses, 68 in central-norway and 32 in Northern-Norway. In addition, SALM owns 50 per cent of Norskott Havbruk AS, a 50/50 joint venture with LSG. Norskott Havbruk in turn owns 100 per cent of Scottish Sea Farms Ltd, UK s second largest producer of salmon. SALM was listed on the Oslo Stock Exchange in 2007 and has approximately 1000 employees. 82 Grieg Seafood (GSF) GSF is Norway s fifth largest salmon company in terms of volume and the company is specialized in salmon and trout which they produce, process and sell. The company has production facilities located in Rogaland and Finnmark, while their international facilities are located in Shetland (UK) and British Columbia (Canada). The company has an annual production capacity of 90 000 tons gutted weight, 100 licenses and over 700 employees. Approximately half of their harvest volume originates from Norway. The company was listed on Oslo Stock Exchange in 2007. 83 81 www.marineharvest.com/about/ - About Marine Harvest & Products 82 SalMar - Annual Report (2014) pg. 22 & http://www.salmar.no/about-salmar - About SalMar 83 Grieg Seafood - Annual Report (2014) pg. 11 & www.griegseafood.no - About Grieg Seafood 30

3. Financial analysis In order to get an overview of LSG s historical performance, financial wellbeing and where the company has created/destroyed value for their shareholders in the past, we will perform a financial analysis. We will split our analysis into two parts: Profitability and growth, and risk. A good analysis needs to focus on the key areas of financial performance to uncover possible advantages the company might have over their peers, and if these are utilized or are likely to be utilized in the future. The financial analysis will, together with the strategic analysis, lay the foundation for our forecast and valuation later in the thesis. 3.1 Accounting quality To ensure that changes in financial ratios reflects changes in a firm s underlying operations and financial position, reported accounting numbers which are used in our analysis have to be adjusted to make them comparable over time and across firms. 84 In addition, it is important that accounting info is reliable. 3.1.2 Accounting principles LSG s consolidated accounts are submitted in accordance with IFRS and interpretations established by the IASB. Their accounts are based on all compulsory accounting standards (IFRS) as adopted by the EU. The consolidated accounts used for analytical purposes in this thesis have all been given a clean independent auditor report. 3.1.3 Potential red flags LSG has throughout the analyzed period used PWC as their external auditor, and received a clean audit in all years. They have changed their responsible auditor every 4 years within PWC. From 2005-2008 Per Henrik Gillesvik was responsible for signing off on the auditor s report. From 2009-2012 it was Hallvard Aarø, and from 2013 until present time it has been Sturle Døsen. Although, many practitioners believes one should change audit firms every 5 year in order to get a more impartial auditor, we do not view their continuous use of PWC as a red flag, as they are one of the most respectful auditing firms in the world, and it seems to be the normal practice in the industry. 85 84 Petersen & Plenborg, financial statement analysis, page 333. 85 MHG has had the same audit firm from 2006-2014, GSF from 2007-2014. 31

Throughout the analyzed period, the company has reported leased assets as financial leases and thus booked leased equipment in their balance sheet as assets and future payments as liabilities. The company has no significant operational leases. 86 Leases thus do not represent potential red flags for LSG. However, all the firms in the peer group uses operating leases. To deal with this issue, we will capitalize these leases in accordance with Moody s guideline for standard adjustment to capitalize operating leases. 87 The line item other costs are not specified in the annual reports, and are large in magnitude. As a result, the company might hide information from the public in this line item. Furthermore, all the peers specify this line item in further detail in the notes. This raises some suspicion as to why LSG do not. Nevertheless, the line item is similar in size and development as the rest of the peer group, 88 so we do not conclude that there is a red flag present in this line item. Looking closely at all the notes in the annual reports from 2005 to 2014, we cannot find any sources of potential red flags. 3.2 Analytical income statement and balance sheet A robust valuation model requires a clear account of the financial performance of the firm. The main driving force for value creation is the firms core operations. Thus, we need to rearrange the income statement and the balance sheet for LSG and the peers in order to obtain correct measurements for critical financial ratios. The purpose here, is to separate operating items, non-operating items and financial items. Reclassification of accounts leads to new key terms: Invested capital and NOPAT (Net operating profit after tax). You can find analytical income statements and balance sheets for LSG and the peer group in appendix 3.1. 3.2.1 Income statement The following line items have been removed from core operations of LSG: Adjustment of biomass to fair value Accounting of live fish in companies listed on the stock exchange is regulated by IAS 41 Agriculture. The main rule is that such assets, including live fish, shall be valued at market price less estimated sales costs. 89 Value adjustment of biological assets according to IAS 41 causes the book value of inventory and biomass 86 Lerøy Seafood - Annual Reports (2005-2015) note 18. 87 http://www.elfaonline.org/cvweb_elfa/product_downloads/mlac06rtngagen.pdf 88 See section 3.3.2, page 39 89 Lerøy Seafood Annual Report (2014) pg. 72 32

to vary a lot over the year, due to unpredictability when it comes to prices, production factors etc. Over the period analyzed adjustment of biomass to fair value has varied between NOK -615 million to NOK 764 million. Estimating this number is thus a near impossible task, and it has therefore been removed from core operations of the company. This has also been done for peers. Impairment loss LSG perform regular tests to assess possible impairment in the value of goodwill and other intangible assets in order to assess whether the cash generation from these assets and synergies are realistic. They write down the value of these assets, if they find that they are not. It is therefore a line item that will be unpredictable for the future. It is also worth noting that this is a relatively small item, and should not affect the value of LSG in a big way. We have therefore excluded it from core operations of the company. This has also been done for peers. Line items that have been kept in core operations, but are noteworthy are: Other revenues Other revenues are comprised of gains and losses related to sale of operating assets, business combinations, and other current and present operating activities. 90 The line item is also insignificant, and has only been active the last two fiscal years. We have thus chosen to keep it as core operations, as it is related to operating activities. Income from associated units Income from subsidiaries, associates etc. Is mainly income from companies where LSG owns 100% (3 exceptions here they are the majority shareholder), and are companies who works within the salmon industry. 91 These companies have been acquired through M&A activities, and their activities range from farming to sales and distribution in the value chain. It is therefore reasonable to include this income as core operations for LSG. 3.2.2 Balance sheet In order for us to calculate the critical invested capital for LSG and its peers, we need to reorganize the balance sheet. We are here interested in separating their operating assets from their nonoperating assets and financial structure. 92 The reported balance sheet mixes operating and nonoperating assets and 90 Lerøy Seafood - Annual Report (2014) pg. 101 91 Lerøy Seafood - Annual Report (2014) pg. 86 92 Koller et al (2010) Valuation pg. 134 33

liabilities which we need to untangle and reorganize in order to perform a good analysis. To find the invested capital we have used the setup in Petersen and Plenborg. 93 Some noteworthy posts are: Shares in associates Shares in associates has been treated as an operating asset, as a result of consistency with the classification in the income statement, and due to the fact that all the associated companies serve a part in LSG s value chain. Deferred tax assets As the company is making healthy profits, and this line item is relatively small and a result of temporary differences in tax, we find it highly likely that they will realize their deferred tax assets in the near future. We therefore classify this post as an operational asset. Biological assets Biological assets are fish in sea, adjusted to fair value. It can thus be looked at as inventory, and should be treated as an operating asset. We have thus classified it as a current asset. Other receivables Other receivables include refundable VAT, pre-payments, and currency futures and impact of fair value hedging, as well as an item called others. The last part could be reclassified as a security, but seeing how it historically has been a very low part of this line item, and that hedging foreign cash flows can be viewed as a risk management tool supporting LSG core operations (for stability reasons), we have decided to leave it as an operating asset. It is also counter accounted for in other current liabilities, and thus have a very low impact, if any, when invested capital is calculated. We have therefore classified other receivables, in its entirety, as a current asset. Other current liabilities Other current liabilities contains accrued wages and holiday pay, impacts of fair value hedging instruments, accrued interest costs, discounts, and others. For the same reasons as above, we have not moved impacts of fair value hedging from this line item. We have therefore classified other current liabilities as operating liabilities, and put it under non-interest bearing debt in our reformulated balance. Other non-current liabilities This line item mostly consists of fair value adjustment of interest rate swaps, it is therefore natural to classify it as interest bearing debt. 93 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 81. 34

Pension liabilities Pension liabilities are calculated as estimated future payments discounted by a safe bond rate, 94 and are thus interest bearing. We have therefore classified this post as interest bearing debt. Cash and cash equivalents Ideally we would like to split this line item into an operating part needed to support LSG s operations and a financial part. This is a very difficult task because it is not distinguishable in the annual reports. We have therefore followed common practice and treated all cash as excess cash, and thus as a security in the reformulated balance sheet. 3.3 Analysis of historical profitability, growth and performance In order to analyze the historical profitability and performance of LSG we will first look at the operating results and then look at the results through an owner s perspective. The DuPont model as seen in appendix 3.2 will be used for this purpose. Profit is measured over the entire year, while reported balance sheet figures are at a given time. We therefore use average balance sheet numbers to compensate for this effect when calculating key ratios. LSG s operating performance is generated through its core business and is best analyzed through return on invested capital (ROIC), which is the overall profitability measure. 95 A disadvantage with ROIC is that it is not able to explain whether the profitability is driven by good capital utilization or by a good revenue- and expense relation. 96 Because of this, we will analyze the source of value creation from operating activities by decomposing ROIC into profit margin and turnover rate on invested capital. We will also compare ROIC with LSG s WACC, 97 to see whether the company has created value for their stakeholders or not. For the shareholders we will look at Return on equity (ROE) which measures owners accounting return on their investments. 98 The ratio takes both operating and financial leverage into account, and by decomposing ROE into F-Gear and Spread, we will analyze the effect of financial leverage on shareholders value. An index and common size analysis will be performed in order to get a better understanding of the development of LSG s capital utilization. By assessing development of key ratios over time we will be able to identify strengths and weaknesses related to financial performance. 94 Lerøy Seafood - Annual Report (2014) pg. 73 95 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 94 96 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 107 97 WACC is calculated to 7.96% in section 6. 98 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 117 35

Furthermore, we will compare LSG s performance with their peer group and look at the relative performance of key ratios in order to identify advantages or disadvantages compared to their peers. Analysis of growth rates, margins and return across peer group will be valuable inputs to the forecast, since it will help us to identify LSG s position in the salmon industry. For our profitability analysis, we find it appropriate to calculate per KG revenues and costs as it better explains the relationship between revenues and costs in a production volume based industry, and it gives a better overview of how cost efficient LSG is compared to their peers. 3.3.1 Operating result decomposition of ROIC To start our analysis, we will look at LSG s historical after tax ROIC, to determine whether or not they have created value for their owners in the past. Graph 3.1 illustrates the development of LSG s ROIC in the period analyzed. As seen, LSG s ROIC has been very Graph 3.1: Historical ROIC vs WACC volatile through the period. This is a result of the cyclical nature of the industry as well as the correlation between performance and the salmon price, as shown on page 27. Compared to the WACC of 7.96%, 99 the returns are mostly satisfying and LSG have created value for their owners in all of the years except 2007, 2008 and 2012. The main Source: Authors creation/lsg ARs 2005-2014 reason for the low ROIC after-tax these three years was the low salmon prices in the market. 100 The average ROIC of 12.6% in the period is also an indication of value creation for LSG s owners. For the peer group comparison the ROIC has been calculated before tax, due to varying degree of exposure towards foreign tax regimes. Graph 3.2: Historical ROIC LSG and peer group Source: Authors creation/ars LSG, MHG, SALM, GSF 2005-2014 99 Calculated in section 6 100 25.8 NOK in 2007, 26.4 NOK in 2008, and 26.6 NOK in 2012 36

The development of the peer group is very much in line with LSGs, as the industry as a whole is affected by the development in the salmon price. From 2011 to 2013, SALM, LSG and MHG followed the same trend, with similar ROIC s. However, in 2014 SALM continued their improvement, whereas LSG, MHG and GSF experienced a stabilized/declining ROIC. To investigate LSG s development and drop in performance in 2014 further, we will break ROIC into profit margin and turnover rate on invested capital below. 3.3.2 Profit margin Development in revenues LSG has been experiencing an explosive growth in revenue from 2005-2014, and have seen their operating revenues more than quadruple. The CAGR for the period has been 13.5%. At the same time, their harvest volume has increased from 52 000 to 158 300. As mentioned earlier, the price development of salmon, has been overall positive in the period, and is the reason why revenues have grown at a more rapid pace than harvest volume. 101 Even though LSG has experienced rapid growth, they are below the peer average of 24.8% CAGR. To analyze operating revenue further and to compare it with the industry, we will look at revenue per kilogram over the period. We can see that LSG have consistently outperformed the market when it comes to operating revenue per kilogram. From the graph we can also see that the market participants follow the same development, which is highly affected by the underlying price of salmon. 102 One notable observation is SALM s drop in 2014, when all other companies remained stable or increased their revenue per kilogram This is likely a result of 19 new licenses gained through M&A activities and restructuring these businesses (i.e. Selling of slaughter ready salmon at spot price, instead of transporting them to their VAP facilities, this is also reflected in a lower COGS per KG this year.) The analysis of operating revenue per kilogram also reveals that LSG s operating revenue is less dependent on the underlying salmon price, and is less volatile than the rest of the peer group. 103 Graph 3.3: Operating revenue per kg, LSG and peer group Source: Authors creation, ARs LSG and peers 2005-2014 101 The average salmon price was 25.7kr per KG in 2005 vs. 40.3 in 2014. 102 The development in operating revenue per KG from 2010 to 2014 is a result of a drop in the salmon price of 15.2% and 18.5% in the first two years, followed by an increase of 39.8% and 1.8% in 2013 and 2014 respectively. 103 LSG s operating revenue per kilogram has a standard deviation of 0.12 compared to an average of 0.25, see appendix 3.5 for calculations. 37

Development in operating costs In line with operating revenues, operating costs has also experienced rapid growth over the analyzed period. LSG s costs are summarized in the table below. Operating cost per KG 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Cost of sold goods -62,6-55,1-52,9-46,2-46,5-48,0-42,9-42,0-46,8-50,6 Salaries and other personnel costs -4,7-5,4-6,5-7,2-6,4-6,7-7,1-6,7-7,6-8,0 Other operating costs -3,7-4,6-5,3-6,2-5,4-5,9-6,3-5,6-6,9-8,0 Total operating costs -71,0-65,1-64,7-59,6-58,2-60,6-56,3-54,3-61,3-66,6 Cost of goods sold (COGS) has varied a great deal over the period and is highly affected by feed prices, as shown in table 2.2 on page 17. As a result of their high VAP and distribution activities, feed costs is less significant for LSG than for other producers, but it is still the most prominent factor on the cost side. 104 COGS was downward sloping from 2005 to 2009, which is likely to be a result of efficiency in production after high M&A activities in 2005-2007. 105 In 2010 there was a jump in COGS as a result of severe biological issues related to Pancreas Disease in Western Norway, leading to higher EBIT costs per kg as a result of low harvest weight. 106 This was enhanced by their acquisition of Sjøtroll Havbruk in the same region. 107 The item declined the following two years as a result of better disease control and farming conditions. In 2013 COGS increased as a result of challenging breeding conditions in central Norway, and an outbreak of amoebic gill disease resulting in lower average slaughter weight, as well as an increase in feed costs. 108 The increase in COGS in 2014 was again a result of higher feed prices, as well as higher costs related to treatment of sea lice. 109 Source: Compiled by authors', annual reports LSG 2005-2014 The rise in feed costs the last two years was in large a result of el nino in Peru, which led to a decrease in fish supply for feed material. This raised the input price for feed producers, which they in turn transferred to the fish farming industry. 110 Table 3.1: Historical operating costs per kg, LSG Salaries and other personnel costs have been rising steadily throughout the period. This is a result of LSG s strengthened focus on VAP and buying and selling activities. This steady increase has caused LSG and other salmon farmers to change toward more hired personnel at production facilities in order to better match the cyclical nature of the industry. 111 This resulted in a 57% increase in hired personnel from 2013 to 2014. 112 This will make LSG and the other peers more robust and flexible when it comes to personnel costs in the 104 Lerøy seafood - Annual Report (2014) pg. 30 105 LSG acquired and merged 7 companies in this period, Annual Report (2014) pg. 5 106 Marine Harvest Handbook (2014) pg. 35 107 Lerøy Seafood Annual Report (2010) pg. 25 108 Lerøy Seafood Annual Report (2013) pg. 20-21 109 Lerøy Seafood Annual Report (2014) pg. 15 110 FondsFinans Aqua sector report (10.04.2015) pg. 25 111 http://www.ilaks.no/for-lite-fisk-til-storslakteri/, http://www.adressa.no/nyheter/okonomi/article8919995.ece 112 Lerøy Seafood Annual Report (2014) pg. 104 38

future. LSG and MHG have similar costs and development here, while GSF and SALM have lower costs, as they focus more on cost-efficient production as opposed to VAP. Other operating costs have also been rising throughout the period. Seeing how LSG do not disclose information about this item, it is hard to say what has caused the rise in this item. However, the item has been raising for all participants in the industry, 113 meaning that it is likely connected with higher maintenance costs associated with new technology, disease control etc. Compared to the industry, LSG has here been performing better than average, and thus satisfactory. Summing up all the operating costs and comparing Graph 3.4: Operating costs per kg, LSG and peer group them with the industry peer group we see that LSG have substantially higher costs per kilogram throughout the period. This is a result of their VAP and buying and selling activities discussed in section 2.6. We also see that all companies somewhat follow the same trend, which is a result of the same factors affecting the cost levels of all participants. LSG and MHG costs look particularly similar, which is expected as they are both more Source: Authors creation, ARs LSG and peers 2005-2014 involved in VAP and buying and selling activities. Another interesting finding is that SALM was the only company who in 2014 managed to reduce costs. As mentioned on page 37, this was a result of acquiring new licenses and restructuring measures. EBIT Even though LSG have successfully increased their revenues over the period, their profit margin is characterized by high volatility. This is a result of volatility in both revenues and costs. From 2008 until 2010 they experienced an increased profit margin as a result of rising revenue per kg, 114 combined with a steady cost per kg. In 2011 and Graph 3.5: EBIT margin, LSG and peer group Source: Authors creation, ARs LSG and peers 2005-2014 113 See appendix 3.1 114 Which was driven by an increase in salmon prices both years 39

2012 the development was negative as a result of lower revenue per kg. 115 The reduction in profit margin was slowed down by a positive development in costs per kg in both years. The rise from 2012 to 2013 was due to much higher revenue per kg, and they managed to double their profit margin despite incurring higher production costs per kg this year. The fall in 2014 was caused by higher costs outweighing the positive effects of an increase in revenues per kg. Overall, the peer group follows the same trend as LSG. SALM is the industry leader, with an average profit margin of 24.8%, compared to LSG s 12.1%. However, LSG and the rest of the peer group have closed the gap in recent years. 3.3.3 Turnover rate invested capital The turnover rate on invested capital expresses a company s ability to utilize the invested capital, and all things being equal, it is attractive to have a high turnover rate on invested capital. 116 Fish-farming companies have a high degree of investments related to biological assets, buildings and equipment, real estate, operating accessories and licenses, and the industry is therefore characterized by a low turnover rate. Graph 3.6: Turnover rate Invested Capital, LSG and peers Source: Authors creation/ars LSG, MHG, SALM, GSF 2005-2014 The turnover rate for LSG declined from 2006 to 2008 and have since then been somewhat steady. The decline was a result of LSG s tripled long term debt and infusion of capital due to investments, strategic partnerships and acquisitions. 117 Similar events have accrued through the analytical period, but not in the same size. LSG has historically had significantly higher turnover rate on invested capital than its peer group, with an average turnover rate of 1.35, compared to an industry average of 0.93. The high utilization of its invested capital is a consequence of LSG s VAP and buying and selling activities, which consequently has led to higher revenues without making further investments in licenses, biomass and farming facilities. In order to analyze this further we will include an index and common size analysis of the invested capital. 115 A drop in the salmon price from 37.3 in 2010 to 32.0 and 25.6 in 2011 and 2012, was the main reason for the negative development. 116 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 108 117 Lerøy Seafood - Annual Report (2014) pg. 5 Important strategic events since year 2000 40

3.3.4 Index and common-size analysis of Invested capital The index and common-size analysis of LSG and its peer group is shown in appendix 3.3. The analyses show that invested capital primarily consists of biological assets, licenses and rights, goodwill and buildings, and real estate and operating accessories. As a result of an industry where companies have started to utilize all of their licenses efficiently, combined with fewer opportunities to increase their production capacity organically, the peer group has invested heavily in licenses, R&D and acquisitions throughout the period. The NWC is almost equal among the peer group, and LSG s change in NWC has mainly been affected by biological assets. Fluctuations in biological assets from 2010-2014 can be explained by the rule that live fish shall be valued at fair value less estimated sales cost. Buildings, real estate and operating accessories have also increased due to their increasing investments in order to sustain higher future growth. Licenses and rights have decreased in recent year because of no new licenses being acquired in the period 2010-2013. The line item is booked in the balance sheet at cost price minus impairment losses. Goodwill has also decreased in recent year, due to lower acquisition activity. Graph 3.7: Indexed invested capital, LSG and peers Source: Authors creation/ars LSG, MHG, SALM, GSF 2005-2014 SALM is the company with the highest growth in the period, increasing invested capital by 841%. MHG s major jump in invested capital at the start is due to acquisitions and mergers undertaken by Geveran Trading Ltd, which bought Marine Harvest, Fjord Seafood AS and Pan Fish AS before they merged all the companies in 2007. 118 In comparison, LSG have increased its invested capital with 600%, the lowest together with GSF. In absolute numbers, LSG is the second largest company in terms of invested capital behind MHG, which has an invested capital of 26.1 billion NOK compared to LSG s 10.0 bn. In recent years the peer group has done profitable investments and has raised their earning potential through slowly increasing their turnover rates. Going forward we expect this trend to continue, as there will 118 Marine Harvest - Annual Report (2014) pg. 71 41

be less possibilities for larger companies to be assigned new licenses as well as less M&A activities due to the market becoming more consolidated. 119 3.3.5 FGEAR A company s financial gearing (FGEAR) explains how a company s assets are funded through equity and debt. 120 NIBD is measured by the difference between interest-bearing debt and interest-bearing assets, and calculations for all companies can be found in appendix 3.4. FGEAR LSG 2006 2007 2008 2009 2010 2011 2012 2013 2014 FGEAR 0,51 0,52 0,51 0,44 0,26 0,24 0,33 0,33 0,27 Source: Compiled by authors', annual reports LSG 2005-2014 Table 3.2 shows that LSG started to decreased its leverage in 2009. This a result of a financial goal implemented by LSG in 2010 stating that the company at all times must maintain a satisfactory financial preparedness in order to have a flexible and sustainable source of financing. 121 The financial goal stipulates that the Group s equity ratio should be at least 30% over time a goal the group has been able to achieve following their strategy change in 2010. Table 3.3: FGEAR peer group FGEAR 2006 2007 2008 2009 2010 2011 2012 2013 2014 MHG 0,56 0,52 0,65 0,62 0,46 0,57 0,59 0,55 0,75 SALM 0,96 0,74 0,71 0,74 0,74 1,01 1,13 0,62 0,43 GSF 1,48 1,01 1,27 1,29 0,74 0,71 0,98 0,91 0,79 Source: Compiled by authors', annual reports 2005-2014 LSG s strategy of lower debt financing, and more flexibility, seem to be the norm and trend in the industry, as seen in table 3.3. While MHG have had a stable source of financing, SALM and GSF have previously funded their acquisitions and investment activities through debt, while they now rely more on equity financing. SALM increased their equity ratio to 51% in 2013, in accordance with new objectives, strategy and risk profile. 122 GSF also increased their equity to strengthen their capital base and reduce their financial gearing in 2010. 123 Table 3.2: FGEAR LSG 119 The 4 largest companies in Norway now have approx. 60% market share, compared to 23% in 2005. 120 Petersen & Plenborg (2012) - Financial Statement Analysis pg.117-121 Lerøy Seafood - Annual Report (2010) pg. 11 122 SalMar - Annual Report (2013) pg. 15 123 Grieg Seafood - Annual Report (2010) pg. 4 42

3.3.6 SPREAD The spread is calculated in order to see whether or not the financial leverage is creating value for its shareholders. 124 Leverage only increases the shareholders value if the spread is positive i.e. ROIC is higher than net borrowing cost (NBC). Table 3.4: Spread LSG Spread, LSG 2006 2007 2008 2009 2010 2011 2012 2013 2014 NBC 3,3 % 3,3 % 6,0 % 3,6 % 3,6 % 4,0 % 3,6 % 3,5 % 4,4 % Spread 19,2 % 3,6 % -1,3 % 9,3 % 15,7 % 7,9 % 1,1 % 12,0 % 10,2 % Source: Compiled by authors', annual reports LSG 2005-2014 As seen from table 3.4, LSG s NBC have been fairly low and stable over the period, resulting in a positive spread in all years except for 2008, when the NBC reached its highest level (6.0%). 125 LSG have therefore been able to create value for their shareholders through their financial gearing. 3.4 ROE Owners perspective The previously analyzed key ratios can be summarized in Return On Equity (ROE). 126 Graph 3.8 illustrates that LSG s ROE has been satisfying, as they have the second highest in the period. In section 6, we calculate required return on equity to be 9.01%, which LSG has been above in every year except 2008 and 2012. LSG s ROE has historically affected the stock price, which can be found on page 18. The weak ROE in 2008 and 2012 was followed by a decline in the stock price, while increasing ROE in 2010, 2013 and 2014 was followed by increasing stock price. LSG s profit margin has followed the cycle of the industry while their turnover rate has been stable in recent years. Except from MHG, all peers have decreased their FGEAR. As a result of this, LSG and SALM have created value for its shareholders in most years, while MHG and GSF have had more variable results. In 2014 LSG, SALM and MHG saw a small decrease in Graph 3.8: ROE after tax, LSG and peer group Source: Authors creation/ars LSG, MHG, SALM, GSF 2005-2014 124 Petersen & Plenborg (2012) - Financial Statement Analysis pg.118, Spread = ROIC - NBC. NBC is the sum of financial income and financial expenses 125 A result of increasing NIBD from 399 mill NOK in 2005 to 2 119 mill NOK in 2008 associated with M&A activities 126 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 118, ROE = ROIC + Spread * FGEAR 43

ROE, and GSF had the highest increase. Higher costs per KG related to diseases are the reason for LSG s decline this year. 3.5 Liquidity analysis In the liquidity analysis we will look at the short- and long term liquidity risk of LSG and its peer group to get a better understanding about their abilities to meet its financial obligations in the future. The seafood industry is cyclical and good liquidity therefore very important to deal with the volatility in earnings. Without sufficient liquidity a company cannot pay its obligations, carry out profitable investments and in worst case it could lead to bankruptcy. 127 3.5.1 Short-term liquidity risk The quick ratio will be used to measure the short term liquidity. The quick ratio indicates how many times the most liquid assets cover the current liabilities. 128 its peer group. Table 3.5: Short-term liquidity ratios, LSG and peer group 2010 2011 2012 2013 2014 2010 2011 2012 2013 2014 Quick Ratio Avg. Liquidity Cycle Avg. 1,8 2,0 1,9 1,5 1,7 1,8 LSG 113 96 122 138 117 117 1,2 1,1 1,3 1,4 1,1 1,2 MHG 194 155 152 211 160 174 1,0 1,1 1,0 2,4 1,1 1,3 SALM 170 156 194 193 165 176 1,4 1,2 1,3 1,0 0,9 1,1 GSF 239 244 214 251 233 236 1,4 1,3 1,4 1,5 1,2 1,3 Avg. 179 163 170 198 169 176 Days Sales Outstanding Avg. Days Payables Outstanding Avg. 49 43 48 61 50 50 LSG 43 42 46 55 46 46 64 57 56 81 64 65 MHG 68 64 55 82 54 65 58 62 79 51 60 62 SALM 67 63 103 56 45 67 46 51 31 35 43 41 GSF 99 124 75 120 95 103 54 53 54 57 54 54 Avg. 69 73 70 78 60 70 Source: compiled by authors', annual reports LSG and peers 2009-2014 Table 3.5 shows LSG s short term ratios together with LSG has the most solid quick ratio throughout the period, even though they had a decrease from 2012-2013 due to an increase in current liabilities of 47%. This can also be seen in the increased day s sales 127 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 150 128 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 155-44

outstanding which went from 48 days to 60 days in 2013. 129 The total level of the peer group is rather low compared to the rule of thumb which indicates that a company should have low liquidity risk with a quick ratio around 2. It does not look like this rule of thumb applies in the salmon industry. Another measurement for short term liquidity risk is the liquidity cycle, which indicates how many days it takes to convert inventory into cash. 130 LSG s liquidity cycle has been the lowest in every year and the average is 117 days, which is much lower than the peers who have average liquidity cycles between 174 and 176 days. LSG has accomplished this by having good control of its working capital while increasing their earnings. By looking at the numbers, LSG is also the company with lowest volatility, and seem like a safely ran company based on days payable outstanding (DPO). 131 This could lead to cheaper and easier access debt financing. The reason why it takes so long to convert inventory into cash overall in the industry, is because of the long production cycle of salmon, discussed in section 2.1.4. 3.5.2 Long-term liquidity The long-term liquidity will be measured by solvency ratio and interest coverage ratio, and can be found in table 3.6. A low solvency ratio indicates high long-term liquidity risk. 132 The historical numbers of LSG shows that the solvency ratio has been higher and more stable compared to the peer group. Based on the solvency ratio, we deem LSG s long-term liquidity to be low. Table 3.6: Long-term liquidity ratios, LSG and peer group 2010 2011 2012 2013 2014 Avg. 2010 2011 2012 2013 2014 Avg.* Solvency Ratio Inverest Coverage Ratio 0,8 0,8 0,7 0,8 0,8 0,8 LSG 25,8 15,1 5,3 17,9 15,7 16,0 0,7 0,6 0,7 0,6 0,5 0,6 MHG 15,5-25,8 2,9 2,7 2,0 5,8 0,6 0,4 0,5 0,7 0,7 0,6 SALM 25,5 5,7 3,3-7,2 17,1 12,9 0,6 0,5 0,5 0,6 0,6 0,6 GSF* -333,7 7,3-1,5 4,8 6,0 4,1 0,7 0,6 0,6 0,7 0,6 0,6 Avg. -66,7 0,6 2,5 4,6 10,2 9,7 Source: compiled by authors', annual reports LSG and peers 2009-2014 * High minuses not included when calculating average The interest coverage ratio measures the ability of a company to cover its net financial expenses. 133 An 129 130 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 153-154 - 131 132 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 158-133 45

average interest coverage ratio of 16 indicates that LSG have good coverage to pay their interest expenses, and thus they do not exhibit high financial risk. The good liquidity ratios of LSG are explained by their financial department that monitors the prognoses of the liquidity requirements. The department is ensuring that LSG have sufficient cash equivalent to fulfill operating commitments while sustaining a sufficient level of flexibility. 134 The most significant individual factor related to liquidity risk is fluctuations in the salmon price. Liquidity is also affected by fluctuations in production and slaughter volumes and changes in feed prices, which is the most prominent single factor on the cost side. 135 In view of the above liquidity analysis, where LSG have shown low risk and steady ratios compared to its peer group, we consider the future liquidity risk to be low on short- and long term. LSG s equity ratio, prospects for future positive results and the conservative debt financing will enable LSG to conduct future investments, even in cycle-downturns. LSG expectation of low liquidity risk in the future is also justified by the good prospects for both salmon prices and capacity expansion. The full risk assessment can be seen in appendix 6.4 134 Lerøy Seafood - Annual Report (2014) pg. 74 135 Lerøy Seafood - Annual Report (2014) pg. 30 46

3.5 Conclusion financial analysis We have summarized LSG s historical performance in the table below. Table 3.7: Financial statement summary, strength and weaknesses Strengths Weaknesses - Highest turnover rate in the industry - Highest costs in the industry - Second highest ROIC in the industry - High volatility in returns - Highest revenue per KG in the industry - Among the lowest EBIT margins - Strongest liquidity in the industry - Lowest volatility in the industry Source: Authors creation - Earnings and profitability dependent on one commodity. As a final overview of the industry, we have created a profitability map which indicates where a company is headed based on its profit margin and turnover rate on invested capital. 136 Using the last three years, a pattern emerges summarizing our previous sections and indicating a higher profitability and turnover rate as a result of higher salmon prices and profitable investments. Graph 3.9: Profitability map, LSG and peer group Source: Authors creation 136 Koller,T. Goedhart,M. and Wessels,D. (2010) Valuation pg. 215 47

4. Strategic analysis In this section we will analyze LSG s strategic performance and outlook, challenges, and the environment in which they operate. First we will look at LSG s strategy, development of non-financial value drivers, and strategic measures for the future through a VRIO analysis. We will then examine how industry specific factors will affect the industry and LSG trough Porter s five forces model. Lastly, we will analyze macro factors that affect the industry and LSG by performing a PESTEL analysis, as well as a salmon price analysis. Through these analyses, we want to answer the following questions: Which key factors influence the LSG s cash flows and profitability? What key factors influence the industry s cash flows and profitability? Does LSG have a competitive advantage/disadvantage, and what are they? At the end we will conclude, and combine our findings in the strategic analysis with our findings in the financial analysis, and summarize all of our analyses in a SWOT matrix in order to get a better understanding of LSG s current competitive position and outlook for the future through looking at their strengths, weaknesses, opportunities and treats. 4.1 VRIO analysis To examine potential competitive advantages in the past and future, we will look at the steps in LSG s value chain, their resources and the firm s strategy using Barney s VRIO framework, first laid out in his 1991 paper Firm resources and sustained competitive advantage. According to Barney, a firm is said to have a competitive advantage when it is implementing a value creating strategy not simultaneously being implemented by any current or potential competitor. A firm will exhibit a sustained competitive advantage when it is implementing a value creating strategy not simultaneously being implemented by any current or potential competitors and when these other firms are unable to duplicate the benefits of this strategy. 137 Furthermore, a resource has to be Valuable, Rare, Imperfectly imitable, and supported by Organization in order to be classified as a lasting competitive advantage. Resources are divided into three groups: Physical, human and organizational. In this thesis, we will focus on the physical assets of the company, and treat human and organizational resources as support for these main resources. We will go through the analysis, by assessing LSG s competitive position and outlook at each step in the value chain. 137 Barney, Jay (1991). Firm Resources and Sustained Competitive Advantage, Vol 17, No. 1. Journal of Managements 48

Roe and smolt production The first step in the value chain lay the foundation of the entire production cycle of salmon. LSG goes to great length in order to ensure the healthiest possible egg and roe, by selecting the highest quality fish for breeding purposes. They are also self-sufficient when it comes to egg and smolt production, as mention on page 21. In line with their overall strategy of cutting costs, LSG have made significant investments in new smolt facilities in an effort to produce bigger smolt, closer to the farming sites, which will reduce the time at sea for salmon, reduce risk of diseases, and make the production more cost efficient. 138 They have also invested substantial amounts in cleaner fish, such as lump fish, to reach their goal of more cost efficient production. 139 In addition to cutting future costs, these factors are expected to contribute to a shorter production cycle in the future. LSG also launched their first closed aquaculture farm (preline) in early February 2015, and the first generation of smolt was put into the site in March, 2015. The system is made to protect the smolt from parasite and undesirable elements during the early stage of their development. 140 With this new technology, smolt will grow from 80-100 gram to 0.5-1 KG before they are released to sea. The preline system has the potential to be very valuable in the short and long-term, as LSG will have more control over the development of young salmonids, diseases and will contribute to a shorter production cycle. MHG is the only other peer that is working on a similar project, 141 while the other peers have stated that they focus on optimizing the smolt environment in early stages in fresh water, and produce larger smolt at land. 142 This can thus be seen as a rare resource, as not all players in the industry possess the same technology. This technology is supported by the organization, by their vision of being a sustainable fish-farming company, and by being an industry leader within research and development. Overall, LSG has been performing average in this step of the value chain, but the new technology introduced earlier this year might lead to a temporary or sustainable advantage. This leads us to upgrade the performance outlook to average/good. Farming and harvesting Farming and harvesting and the efficiency herein is a critical step in the value chain. It affects the 138 Lerøy Seafood - Annual Report (2014) pg. 8, 9 & 13 139 Lerøy Seafood - Annual Report (2014) pg. 9 & 15 140 https://www.leroyseafood.com/en/investor/about-leroy/news/2014/breaking-new-ground-in-aquaculture/ 141 Marine Harvest Annual Report (2014) pg. 30 142 SalMar - Annual Report (2014) pg. 18, Grieg Seafood - www.griegseafood.no/production/technology 49

companies ability to turn production input (smolt) into revenue. To measure efficiency 143 of farming and harvesting, we will examine the historic performance of LSG and later compare it to that of the industry. Our findings are summarized in the table below. Table 4.1 Yield per license, LSG Efficiency, LSG 2009 2010 2011 2102 2013 2014 Licenses 105 130 130 130 130 141 Harvest volume 108 500 116 800 136 600 153 400 144 800 158 300 Yield per licens 1 033 898 1 051 1 180 1 114 1 123 Source: Compiled by authors', Annual reports LSG 2009-2014 As seen from the table above, LSG s efficiency has been varying over the period. They started with a negative trend from 2009 to 2010; this was a result of a high increase of new license, which naturally yields lower harvest volumes in the start. 144 The yield then had a positive development, before it fell in 2013, as a result of challenging conditions and problems with diseases, as discussed on page 38. These problems continued in 2014, but LSG managed to raise their yield slightly. Graph 4.1: Yield per license, LSG and peer group Source: Compiled by authors, Annual reports 2009-2014 LSG have been performing around the industry average for the period, but if we remove GSF from the analysis, they drop well below average. SALM is clearly the most efficient producer in the industry, while LSG and MHG have similar efficiency. Last year though, LSG remained stable whereas MHG managed to raise their efficiency considerably. With an expected annual harvest quantity of around 1 200 tonnes HOG per license, 145 LSG have also been performing worse than expectations throughout the period. One reason for LSG s bad performance is that they have a larger part of their operations in western Norway than the rest of the peer group, where the conditions have been challenging in recent years. 146 143 Measured as yield per license 144 The production cycle for salmon is normally 2-3 years 145 Marine Harvest Handbook (2014) pg. 53 146 LSG - Annual Report (2014) pg. 16, SALM - Annual Report (2014) pg. 4, MHG - Annual Report (2014) pg. 48 50

With the above analysis in mind, we conclude that farming/harvesting is an extremely valuable resource for LSG, it is not rare in the industry, nor imperfectly imitable, and the resource is supported by the organization. LSG s performance in this step in the value chain has been below par, but recent development and measures has been undertaken to deal with the bad performance. We thus conclude that the performance has been average/bad, but expect it to be fixed in the medium-long term, as it is an element of their strategy to decrease diseases and costs, and produce larger smolt, which in turn will lead to higher efficiency and yield per license. Production and VAP To assess this step of the value chain, we will focus on key production facilities and aspects of LSG s strategy, and leave some out of the discussion these are mostly production facilities and aspects that we deem to be of neutral performance, and thus do not give room for competitive advantages or disadvantages. Lerøy Aurora Lerøy Aurora is located at Skjervøy in Troms County. They have has one of the most modern processing facilities in Norway, and is a significant supplier to external customers. 147 Specifically, they produce LSG s products for the Japanese market, which consists of raw products like sushi and sashimi. The infrastructure is built such that it only takes 36 hours from the packing station to the Japanese market, 148 helping them to become Norway s largest supplier of sushi. Aurora salmon is also sold in Singapore and China. Lerøy aurora and the sushi segment are very valuable to LSG. Specifically, their sushi segment is extremely valuable as it has a very high profit margin compared to whole salmon. The company had revenues of 1 190 million and an EBIT of 370 million in 2104 an EBIT margin of 31%, down from 35% the year before. 149 Furthermore, they are well positioned to take advantage of the expected quadrupling in Chinese salmon consumption, where 80% of the increase is expected to be consumed as raw fish. 150 Their integrated and fast track export to Japan and Asia is deemed as a rare resource for LSG. SALM and MHG both have their own brand of sushi products, but as LSG is the industry leader in this segment, we see LSG s sushi production and Lerøy Aurora as a rare resource, which is not easily imitated. LSG have the entire infrastructure in place to take advantage of this resource, and it is a part of LSG s differentiated strategy. 147 Lerøy Seafood - Annual Report (2014) pg. 15 148 https://www.leroyseafood.com/en/business/products/key-brands/aurora-salmon/ 149 Lerøy Seafood (Q4 Report) pg. 24 150 Implement Consulting Group How Norway disrupted sushi 51

We therefore conclude that Lerøy Aurora is a temporary, and possibly, a sustainable competitive advantage for LSG going forward. The company will also contribute to a sustained high sales premium in the future. VAP and product innovation Product innovation has been at the heart of LSG s strategy for a long time. 151 Their products and distribution methods have several times been awarded prizes, and been celebrated around the world. 152 To analyze their performance more in detail, we measure their achieved per kg price against the average spot price, and compare it to that of the industry. Our findings are summarized in the table below: Sales premium LSG As seen in the table above, LSG have continuously attained a higher premium than the industry average, which we in section 3.3.2 (pg. 37) found led to an uncontested high price per kg attained in the market. We can thus see that their VAP activities and innovative product lines are being well received in the market, and they are able to charge more for their products than their peers. It is also notable that the second highest 5-year average premium in the market is obtained by MHG, with a premium of 1.5. This must thus be seen as a very valuable resource for the company, which is likely hard to imitate and thus rare in the industry, since no other company mange to achieve the same price. The foundation and organizational structure is very much in place throughout the company to take advantage of this resource, and it is also visible through their strategy. We therefore conclude that their product innovation and VAP activities has given and will continue to give LSG a sustainable competitive advantage in the future. Lerøy Seafood Group 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating income 5 616 592 6 290 898 6 057 053 7 473 807 8 887 671 9 176 873 9 102 941 10 764 714 12 579 465 Avg salmon price 32,3 25,8 26,4 30,9 37,3 32,0 26,6 39,6 40,3 32,3 35,1 Avg achieved price 75,4 70,8 65,3 68,9 76,1 67,2 59,3 74,3 79,5 70,8 71,3 Sales premium 2,33 2,75 2,48 2,23 2,04 2,10 2,23 1,88 1,97 2,22 2,04 Sales premium Industry average 2006 2007 2008 2009 2010 2011 2012 2013 2014 industry Operating income 3 258 379 5 767 435 5 681 306 6 520 547 7 503 807 7 789 217 7 688 455 9 643 634 11 926 290 Avg salmon price 32,3 25,7 26,4 30,9 37,4 31,8 26,6 39,6 40,4 32,3 35,1 Avg achieved price 43,0 40,9 40,3 44,4 52,3 46,2 42,2 56,4 58,0 47,1 51,0 Sales premium 1,33 1,59 1,53 1,43 1,40 1,45 1,59 1,43 1,43 1,46 1,46 Source: Compiled by authors', annual reports LSG and peers 2005-2014 Table 4.2 Sales premiums, LSG and industry Average period Average period Average 5 years Average 5 years Sales and distribution LSG s sales and distribution activities plays a key role in connecting the company to its customers. We will here analyze the parts of this value chain that we find to be of special importance, as we did in the section above. 151 Lerøy Seafood - Annual Report (2014) pg. 11 152 https://www.leroyseafood.com/en/business/products/innovation/ & https://www.leroyseafood.com/en/investor/about- Leroy/News/Awarded-the-annual-Export-Price-2015/ 52

Sjømathuset LSG opened up Sjømathuset in March 2014 in partnership with NorgesGruppen Norway s biggest trading company, which specializes in distribution and sale of groceries. Sjømathuset is one Europe s most advanced seafood production facilities with a capacity of 8-10 000 tons and 20 million pieces of sushi. 153 As part of their strategic partnership, NorgesGruppen is sjømathuset s only customer. With fresh food specialist Meny (30% market share in fresh fish segment in Norway) in their portfolio of food chains, this is a very valuable partnership for LSG. Furthermore, sushi is gaining popularity in Norway and the western world. With market demand exploding the last decade and reaching 720 million NOK in 2013, 154 LSG s capacity of 300 000 sushi bites every week is well positioned for this segment. With startup revenue of 415 million NOK in 2014, and a good strategic position in the Norwegian market, this is a very valuable resource for LSG. It is also a rare resource and hard to imitate because of the strategic partnership, and the position in the Norwegian market, which can lead to a first mover advantage. Again, LSG have all the infrastructure and organizational structures in place to support this operation. We expect Sjømathuset to have a positive effect on LSG s revenues, and that the first mover advantage and strategic partnership will lead to a temporary, and possibly a sustainable competitive advantage in the Norwegian market. It will also contribute to uphold a high sales premium for LSG. Hallvard Lerøy AS Hallvard Lerøy is the main sales and distribution company for the group, and has a global reach with offices in Sweden, Finland, France, Spain, Portugal, China, Japan, and USA. They offer a wide range of products to meet the market s need. Their main focus is customer needs and cost-efficient handling of individual clients. 155 Hallvard Lerøy also enables LSG to buy cheap salmon from smaller producers, further develop them before selling them through their distribution network at a premium. 156 Hallvard Lerøy is extremely valuable to LSG, as the company handles most of their sales. The industry peers, also have distribution channels in place to sell their salmon, so it cannot be seen as rare. However, none of the other peers seem to be able to match the premium generated as a result of LSG s innovation and distribution through Hallvard Lerøy, and we therefore deem it to be somewhat imperfectly imitable. As a key step in LSG s value chain, and through strategic partnerships and fish-cuts around the world, Hallvard Lerøy is supported throughout the organization. 153 https://www.leroyseafood.com/en/investor/about-leroy/news/2014/sjomathuset/ 154 http://www.dagbladet.no/2014/05/18/nyheter/innenriks/fisk/taco/sushi/33362182/ 155 https://www.leroyseafood.com/en/business/about-us/worldwide-distribution/ 156 They sold 220 000 tonnes, compared to a total harvest volume of 178 100, including associates harvest volumes 53

Overall Hallvard Lerøy is an important part of the value creation for LSG, and one of the driving forces behind their uncontested high sales premium, and thus gives room for a temporary advantage. However, it comes at a higher cost than what their peers incur, as discussed in section 3.3.2 (pg. 39). We therefore downgrade the competitive implication to neutral/temporary advantage in the future, and the performance to neutral/good. 4.1.1 Summary VRIO analysis Figure 4.1: summary VRIO analysis Step in valuechain Roe/Smolt production Resource Valuable? Rare? Egg production Smolt Preline yes yes yes no no yes Imperfectly imitable? no no yes Supported by organization? yes yes yes Performance Average Average Good Competitive implication Neutral Neutral possible advantage Value chain outlook Average/ Good Farming & harvesting Farming yes no Harvesting yes no no yes no yes Average/bad Average/bad Neutral/Temp. disadvantage Neutral/Temp. disadvantage Average Production & VAP Lerøy Aurora Product innovation Fish-cuts yes yes yes yes yes no yes no no yes yes yes Good Good Average Temp./sustain. Advantage Temp./sustain. Advantage neutral Good Sales & distribution Sjømathuset Halvard Lerøy yes yes yes yes yes no somewhat yes Good Neutral/good Temp./sustain. Advantage neutral/temp. Advantage Good Source: Authors' creation In conclusion, LSG s strategic measures have put them in a good position going forward. Specifically, they are in a good position to maintain their high sales premium. Further, Investments made are expected to raise their efficiency and decrease costs. However, new cleaner fish and technology will incur higher costs, and offset some of these effects. 4.2 Porter s five forces Industry structure drives competition and thus profitability in an industry, and generally a high level of competitiveness drives the profitability down to a level where investors are unable to make abnormal 54

returns. 157 To examine the structure further, and to get a better understanding of what shapes the nature of competition within the seafood industry, we will use the theoretically acclaimed five forces model, originally published and further developed by Michael E Porter. 158 The model can be found in appendix 4.1. 4.2.1 Threat of new entrants When new entrants enters or threatens to enter an industry, the profitability of that industry becomes capped as a result of the existing companies reply to the threat. When the threat is high, existing companies lowers their prices and/or expand investments in order to deter new entrants. This leads to pressure on prices, costs, and rate of investment. 159 It is the threat of entry, not entry itself that sets these effects in motion, and thus the threat existing companies face depends heavily on how high the entry barriers in the industry are. There are seven major barriers to entry, and thus advantages existing companies have over potential entrants. 160 These are: supply-side economics of scale, demand-side benefits of scale, customer switching costs, capital requirements, incumbency advantages independent of size, unequal access to distribution channels, and restrictive government policy. We will examine these barriers below. Supply-side economics of scale Our industry analysis revealed that fish farming is associated with a vast amount of invested capital, enhanced technologies, and a well-integrated value chain, as discussed in section 2.2.4 (pg.16). Furthermore, smaller players in the Norwegian market tend to be targets of takeovers, which is evident through the bigger players M&A activity and market share. This forces potential new entrants to enter the market at a very large scale and at a cost disadvantage if they want to compete with the existing companies. We therefore conclude that there is strong evidence of supply-side economies of scale, which deters entrance. Demand-side benefits of scale (network effects) Network effects arise in industries where a buyer s willingness to pay for a product increases with the number of other buyers who also buy the product. In the fish farming industry, we cannot conclude that customers buy LSG s or their current peers products because of these network effect. There is therefore no evidence for demand-side benefits of scale. 157 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 189 158 Porter, Michael (2008). The Five Competitive Forces That Shape Strategy. Harvard Business Review pg. 79 159 Porter, Michael (2008). The Five Competitive Forces That Shape Strategy. Harvard Business Review pg. 80-81 160 Porter, Michael (2008). The Five Competitive Forces That Shape Strategy. Harvard Business Review pg. 81 55

Customer switching costs Salmon is sold to customers either at predetermined rates or at the market spot price. It is thus not hard for customers to switch from one producer to another, and the industry is thus characterized by low customer switching costs. This has a dampening effect on entry barriers. Capital requirements As discussed in section 2.2.4 (pg. 15) there are high capital requirements associated with starting up as a fish farming company. A normal site requires an initial investments of 25-30 million NOK in operating equipment, in addition to four licenses, each with a cost of around 50 million. 161 Furthermore, section 2.2.4 revealed that it takes two to three years to grow ready-to-sell salmon, which means no incoming revenue for a new startup in these first years. This is a big restraint, and it requires a lot of free capital and risk to deal with this period of time without revenues. We therefore conclude that there are high capital requirements associated with starting a company in the industry, which deters entry. Incumbency advantages independent of size To be able to compete in the industry you have to attain the proper licenses to farm salmon. These licenses are highly regulated by the Norwegian government, and hard to attain for a new startup firm a large reason for the vast amount of takeovers in the industry, is to attain new licenses. Moreover, the technologies in the industry are getting more and more advanced, as the big companies look to fully integrate their value-chains, and focus more on sustainable production. The industry thus exhibit Incumbency advantages. Unequal access to distribution channels LSG have access to a unique network of distributors both in Norway and around the world, as discussed in section 2.6 (pg. 24) and 4.1 (pg. 53). LSG use this network in order to distribute their products in an efficient way. The other big players in the industry also have well developed distribution channels for their products, and integrated value chains that give root for scale economies. We therefore conclude that the industry is characterized by unequal access to distribution channels, which deters entry. Restrictive government policy As discussed in section 2.2.3 (pg. 14), there are highly restrictive government policies in place when it comes to the fish farming industry, both in Norway and in other salmon producing countries. These are put in place through licenses, and high requirement when it comes to fish health and environmental factors. This is therefore an important entrance barrier that is an advantage for existing companies in the industry. 161 This will be discussed further in section 5.4.2 (pg. 90) 56

With the above analysis in mind, we conclude that the industry exhibit high entry barriers, and thus very low threat of new entrants. Specifically, there is high entry barriers associated with high capital requirement and risk for new companies, strict government policies in salmon producing countries, and the industry exhibits strong supply-side economics of scale. 4.2.2 The power of suppliers Powerful suppliers capture more of the value created by themselves by charging higher prices, limiting quality or service and/or shifting costs from themselves to industry participants. A supplier group is said to be powerful if: 1) it is more concentrated than the industry it sells to, 2) the supplier group does not depend heavily on the industry for its revenues, 3) industry participants face switching costs when they change supplier(s), 4) offer products that are differentiated, 5) few or non substitutes for what they offer, 6) threaten to enter the industry they are selling to. 162 The industry as a whole is dependent on suppliers when it comes to fish feed. Otherwise, most of the actors in the industry are independent of suppliers due to integrated value chains. The fish feed industry The fish feed industry is highly concentrated and are mostly made up of three major global players: Skretting, EWOS and BioMar. 163 This makes this supplier group powerful, as it is more concentrated than the industry it is selling to. 164 There are not big costs associated with switching from one fish feed producer to another, and most of the players uses more than one supplier of fish feed, 165 which limit their power to some extent. Figure 4.2: Fish feed companies Source: MHG Handbook 2014 However, there are no good substitutes to what they sell, and thus they have power to raise their prices to a point where they make extra profit. This has been done in recent history, and fish feed producers have transferred raw material costs from themselves to their customers in the fish-farming industry. 166 However, in 2014, MHG opened up their own fish feed production, and the Peruvian fish feed producers opened up shop again increasing the supply of raw materials for fish feed. 167 These two factors are 162 Porter, Michael (2008). The Five Competitive Forces That Shape Strategy. Harvard Business Review pg. 82 163 Marine Harvest Handbook (2014) pg. 42 164 The three biggest companies controls 98% of the market, the four biggest fish farmers controls 60% of the salmon market 165 Lerøy Seafood Annual Report (2014) pg. 44 166 Marine Harvest Handbook (2014) pg. 42 57

expected to keep the fish feed prices under control in the future, and prices are estimated to fall back to normal levels. This indicates that if the fish feed producers get too out of line with their pricing, their customer can further integrate their value chain and produce their own fish feed. We conclude that fish feed companies have moderately high bargaining power, and that they historically have use this to transfer raw material costs from themselves to fish farmer, however this trend might not last as fish farmers threatens to integrate their value chains further. 4.2.3 The power of buyers If customers are powerful they can capture value by forcing down prices, demanding better quality or service, and eventually playing industry participants against each other at the expanse of the profitability of the industry. 168 Customers are defined as powerful if: 1) there are few buyers or purchases are in large volumes, 2) the producers are standardized and undifferentiated, 3) low or no switching costs between suppliers. The market for salmon products is worldwide, and range from big grocery store conglomerates to small restaurants to individual consumers. There are thus not many buyers who have power to bargain on the price. Even though the producers are relatively standardized, the salmon spot price is determined in the market as a function largely dependent on supply and demand, meaning that this effect is accounted for in the spot and forward prices. This will be discussed further in section 4.4 (pg. 69) We conclude that buyers have moderate to low bargaining power, and that this is expressed through the spot and forward price of salmon. 167 FondsFinans - Aquaculture Sector Report (10.04.2015) pg. 1 168 Porter, Michael (2008). The Five Competitive Forces That Shape Strategy. Harvard Business Review pg. 83 83 58

4.2.4 The threat of substitutes Threats from substitutes is said to be high if: 1) it offers an attractive price-performance trade-off to the industry s product, 2) low cost of switching to the substitute. 169 Graph 4.2: Relative price development, protein sources Source: MHG Handbook 2014 The biggest threat to the salmon industry is other sources of protein: beef, chicken, pork and lamb. Of these five protein sources, the salmon price has remained the most stable over the past 30 years. It Table 4.3: Salmon vs other protein sources Approx per KG Tesco (UK) Wallm. (US) Germany Japan* Meny(DK) Salmon 15,00 $ 23,50 20,00 1,00 kr 133,00 Beef 22,00 $ 26,00 22,00 1,43 kr 160,00 Pork 8,00 $ 8,90 8,00 0,83 kr 85,00 Chicken 10,00 $ 7,76 8,00 0,23 kr 75,00 Source: compiled by authors', Tesco, Wallmart, Meny, MH handbook 2013 is however the most or second most expensive source of protein in most markets. In addition to protein, salmon offers a rich variety of other nutrients that other protein sources lack, like omega-3, vitamins and minerals. 170 Even though other protein sources tend to be cheaper than salmon, the exploding focus on eating healthy and taking care of one self have had a positive effect for the demand of salmon in recent year, and is expected to continue in the future. We will discuss this further in section 4.3.3 (pg. 66). We conclude that threats from substitute products are medium to high. 4.2.5 Rivalry among existing companies Rivalry among existing companies comes in a variety of forms, from price competition to innovation. The intensity and basis of competition affects the profitability in the industry. 171 An industry exhibit high intensity rivalry when: 1) the industry is less concentrated, 2) growth in the industry is slow, 3) there are 169 Porter, Michael (2008). The Five Competitive Forces That Shape Strategy. Harvard Business Review pg. 84 170 Marine Harvest Handbook (2014) pg. 13 171 Porter, Michael (2008). The Five Competitive Forces That Shape Strategy. Harvard Business Review pg. 85 59

high exit barriers in the industry, 4) companies are very committed to their business and have high aspirations for leadership and goals that go beyond the economic profit. 172 We will first examine the intensity of rivalry in the fish farming industry, before we move on to the basis of competition. The industry in question is very concentrated, with the 10 largest companies in Norway accounting for 70% of the sales where the four analyzed companies in this thesis have a market share of roughly 60%. Meanwhile, the output growth in the industry has been stable over the past decade with a CAGR of around 6%, and is projected to stabilize and grow with a CAGR of 3% per year until 2020. 173 The industry thus exhibit steady growth and is characterized by a few big players controlling a large part of the market. As seen in the financial analysis, the industry is highly profitable, and is facing a growing demand in the market. In addition, participation in the industry demands substantial investments in infrastructure and production facilities, which is evidence of high exit barrier. Furthermore, the fish-farming industry has a long and rich tradition and is part of the culture in Norway, which could lead owners to be very found and attached to their businesses, and thus not willing to separate themselves from the company. Overall, the industry exhibits moderately high intensity when it comes to rivalry among existing companies. The big players control a big part of the industry and are profitable, the market is growing, and players are thus highly unlikely to leave the industry. Competition in form of price competition is the most destructive form of competition when it comes to industry profitability, as it transfers the profits directly from the industry to the customers. Price competition is more likely to occur if: 1) products or services in the industry are near identical and there are few switching costs for buyers, 2) there are high fixed costs and low marginal costs in the industry, 3) efficiency in the industry requires investment in large scale. The industry can be seen as exhibiting a high degree of homogeneity in products, and there are low switching costs for consumers. However, we feel that companies effort to differentiate their products is successful, which is reflected in the price/kg they can obtain in the market. The industry also exhibit large scale production benefits. Although there is evidence that the industry is likely to exhibit price competition with low profitability, we argue that this does not paint the full picture of the industry and the competition therein. As discussed in section 2.2.3 (pg. 14), there is a cap on how much one can produce, which relieves the pressure on the 172 Porter, Michael (2008). The Five Competitive Forces That Shape Strategy. Harvard Business Review pg. 85-86 173 Marine Harvest Handbook (2014) pg. 18 60

price. Also, the salmon price is largely determined by supply and demand where demand growth in recent years has been well above supply growth. The industry is thus not characterized by price competition; instead companies try to differentiate themselves by introducing new product lines or by being costefficient, as discussed in section 2.10 (pg. 29). We conclude that the industry exhibits moderate to high rivalry among existing companies. The rivalry mainly comes from attaining new licenses, efficiency, and product innovation to secure key customers and distributers. 4.2.6 Summary Porter s five forces With the above analyses in mind, we here conclude by giving each of the forces a number indicator, showing how intense the competition is in the industry. We use a scale from 1-10, where 1 is a very low threat level and 10 is a very high threat level for the industry. From the figure we can see that the most threating force is the power of the fish food producers, which affects the cost level of the industry by transferring their own costs to the fish-farming industry. Threat of substitutes are also high, as they are cheaper than salmon. The industry is through high entry barriers protected from new entrants disturbing the profitability Figure 4.3: Summary Porters five forces Source: Authors creation 61

4.3 PESTEL analysis To examine how macro factors affect the industry and LSG, we will perform a PESTEL analysis. We have here chosen to include environmental and legal factors, as they play an important role in the industry. Specifically they play an important role in determining future supply, and will thus affect the future salmon price. The PESTEL framework is shown in figure 4.4. Figure 4.4: PESTEL analysis Source: Authors creation 4.3.1 Political and legal factors Political factors and how government intervenes in the economy has big impacts on how a company and an industry operate. Important political factors for LSG and the fish-farming industry are legislation, and import and export restrictions. Legislation March 20 th 2015, the Norwegian government presented a new plan (white paper) with the objective of increasing farmed production fivefold until 2050; this corresponds to a 4-5% annual growth in harvest volumes. 174 The aim of the white paper is predictable and environmental sustainable growth in Norwegian salmon and trout farming. In the white paper, they laid out a traffic light system which will allow an increase in MAB of 6% biannually, if certain environmental conditions are met. The proposal suggests that the coastline will be divided into 11-13 zones, and each zone will be given either a red, yellow, or green light dependent on sustainability indicators. A red light means a reduction of MAB, 174 Equity research Pareto 62

yellow light means no growth, and a green light will allow an increase of 6% in MAB. The first classifications are expected to be granted in 2017, and affect harvest volumes in 2017/2018. 175 Furthermore, the government approved land based salmon/trout farming in the start of 2015. This makes it possible to breed 1 200 tonnes of salmon in huge water tanks on land, rather than in cages or closed facilities at sea. Two of the challenges with land-based farms are the costs of changing water and the considerable space which is required for the water tanks. But, the benefits are less direct impact on the environment, no salmon escapes, elimination of the problem of lice spread from farmed fish to wild salmon as well as a huge decrease in sea lice. 176 Land-based production is however expected to have no significant effect the next five years, but it will be important for increasing the post-smolt production size from 100g to 250-500g without increasing biological risk. 177 An increase of the post-smolt size will enable salmon farmers to reduce the growing phase at sea and increase the turnover of biomass. It is expected that the increased post-smolt size will reduce the growing phase in the sea from 18-22 months to 14-16, which again means fewer sea lice and less biological pressure on the fish. This is because almost 80% of the biological challenges occur in the secondhalf of the sea lifecycle. Lower production cycle will also enable salmon farmers to reduce their cost by lowering the number of sea lice treatments from 4-5 to 2 per production cycle. 178 Import/export Most of the revenue in the industry comes from export to key markets. The European Union is the most important market accounting for over 50% of the revenues. Norway have several trade agreements in place with the European union, and this market is seen as stable and is assigned low risk when it comes to political stability. Other markets exhibit more political instability, and the industry face political risks in form of trade restriction, import bans, import taxes etc. in historically key markets. Evidence of this is the Chinese trade restriction of Norwegian salmon after the Norwegian Nobel committee decided to award the 2011 Nobel peace prize to the Chinese prisoner Liu Xiaobo, which led to a 70% drop in import of Norwegian salmon. 179 The Chinese government also imposed bans in March 2015, which can considerably limit the import of Norwegian salmon in the near future. 180 In August 2014 Russia introduced a full ban on the 175 Pareto equity research rapport april 2015. 176 Regjeringen (14.01.2015) «Landbasert oppdrett» 177 Post-smolt is the name of the fish when it is growing from a smolt of 100gram in the freshwater towards its first growth phase in the seawater plants 178 Nordea Markets - Sector Seafood Update (25.03.2015) pg. 20 179 Politikken (DK) (11.05.2011) Kina straffer Norge for Nobel-prisen 180 Dagens Næringsliv (22.03.2015) Frykter full stans i Kinas import av norsk laks 63

import of all Norwegian salmon. 181 At the time, Russia accounted for 10% of LSG s revenues which they in turn had to reallocate to other markets over night. It is thus evident that political tension and instability in certain key markets makes the company vulnerable. It is also hard to predict when these bans will occur, and therefore planning and forecasting in these markets is difficult for the industry. 4.3.2 Economic factors Economic factors are factors that have a significant impact on how the company does business and how profitable they can be. Economic growth and demand Real GDP growth is estimated to be stable around 1.9% in the euro zone from 2015 to 2020. 182 The demand for salmon is expected to be at the same level as in 2014 in 2015, while it is expected to pick up in 2016 as a result of new products stimulating demand, and the Russian market opening up for trade again. 183 The expected numbers are 0.1% and 7.4% respectively. In Japan the real GDP growth is expected to be 1.2% in 2016, before it drops down to 0.4% in 2017, and then stabilize at 0.7% from 2018. 184 The US numbers are 3.1% for 2015 and 2016, and then it falls to 2.7% and 2.4% for the next two years, before it stabilize at 2%. 185 The expected demand growth for salmon in the Americas/Asia is expected to be 9.4% in 2015 and 10% in 2016 according to Fondsfinans analyses. As we can see, economic growth is estimated to be stable in key markets, which is seen as positive for LSG and the industry. Also, the demand is expected to rise in the short-term, which is positive for the development of the salmon price. Interest rates Most of LSG s debt is denominated in NOK and have a floating interest rate. Most bank loans in Norway are based on the central bank s key rate plus a spread. The recent economic crisis in Europe, the drop in oil prices, and the subsequently drop in the value of the Norwegian Krone; have pushed the key rate to an alltime low as of April 2015, at 1.25%. 186 This means that companies are able to borrow at a cheap rate, and thus take on more debt to finance profitable projects. Norges Bank projections can be found below: 181 Lerøy Seafood Annual Report (2014) pg. 9 182 http://knoema.com/mewdmh/european-union-gdp-growth-forecast-2015-2020-data-and-charts 183 FondsFinans - Aquaculture Sector Report (10.04.2015) pg. 3 184 http://knoema.com/qhswwkc/japan-gdp-growth-forecast-2015-2019-and-up-to-2060-data-and-charts 185 http://knoema.com/igsdjtg/us-gdp-growth-forecast-2015-2020-and-up-to-2060-data-and-charts 186 http://www.norges-bank.no/pengepolitikk/styringsrenten/ 64

Graph 4.3: Projected key rate Norway Source: Norges bank As seen from the graph above, the rate is expected to drop to 1% this year, before it starts rising in early 2016, and will approach 2% at the end of 2018. We can thus expect debt financing from Norwegian banks to be relatively cheap and stable in the coming years. This means low risk for LSG and the industry regarding interest payments and with upholding debt covenants. It could also be easier to obtain cheap debt financing for profitable projects in the industry. Exchange rates LSG and the fish-farming industry are exposed to considerable currency risk. Only 16.8% of LSG s revenue in 2014 was denominated in NOK, whereas most of the costs are denominated in NOK. It is thus important and common practice that companies within the industry use financial instruments to hedge these risks. LSG uses currency derivatives combined with withdrawals/deposits in multi-currency accounts in order to minimize currency risk. 187 At the same time, Norwegian salmon is sold with NOK as reference price, and foreign market demand is thus sensitive to the exchange rate. In the past year, the Norwegian krone has dropped significantly in price compared to EUR and USD, which has stimulated demand for Norwegian salmon in these regions. It is expected that this is a trend that will continue in the near future. 188 4.3.3 Social Factors Social factors are demographical and social trends in the population that can affect the demand for LSG s products. 187 Lerøy Seafood - Annual Report (2014) pg. 30 188 FondsFinans - Aquaculture Sector Report (10.04.2015) pg. 4 65

Demographical trends The UN estimates that the population will reach approximately 9.6 billion people by 2050, which will require an increase in food production by 70%, 189 and assuming protein consumption per capita stays constant demand for protein will increase by 40%. 190 While water is covering 70% of the planet s surface it only account for 6.5% of the protein sources produced. Land based agricultural opportunities are scares, which open the doors to exploring how to develop the marine environment even further. There are also a growing middleclass in developing countries, such as the BRIC-countries, that will help stimulate the demand for protein sources like salmon in the near and long-term future. Social trends The population in the developed world is becoming more and more health conscious, and diets are highly affected by what is good for you. Salmon contains several health beneficial minerals and vitamins, which other protein sources lack. This fact has already contributed to an increased demand for salmon and other sea food, and is highly likely to continue in the future. Furthermore, Health advisors and governments in Europe and North America recommend people to eat fish at least twice a week. 191 A growing health conscious population in the western world and in developing countries will therefore help stimulate demand for salmon in the future. 4.3.4 Technological factors Technological factors are advances made through research and development activities in the industry. The industry faces strict regulations, with a heavy focus on sustainable development, imposed by the Norwegian government. However, the new regulations changes discussed in section 4.3.1 (pg. 62) give room for growth in sustainably sound areas. It is therefore increasingly important for the industry to comply with these regulations through R&D development and sustainable production. In addition to individual efforts, every company exporting seafood from Norway is obliged to pay 0.3% of their overseas revenue to The Norwegian seafood research fund (FHF) a governmental run research and development organ that focuses on sustainable development and has the underlying goal of making Norway the leading seafood nation. 192 Research and development in the aquaculture sector Investment in R&D is an important source for innovation and production growth. Fish feed, vaccines, IT, genetics and fish cages are some areas of innovation that has been fundamental growth drivers in the fish 189 http://www.un.org/apps/news/story.asp?newsid=45165#.vjohwbcve1s 190 Marine Harvest Handbook (2014) pg. 6 191 Marine Harvest Handbook (2014) pg. 13 192 http://www.fhf.no/om-fhf/ 66

farming industry. These innovations have contributed to higher product quality, higher growth rate, lower production cost and lower mortality. 193 Most of the new technological advances in the industry are easy to copy as it is hard to get a patent protection, or the technology can be purchased by external manufacturers, as well as some is developed in association with FHF to better the industry as a whole. Competitive advantage is therefore created through continuous improvement and rapid adoption of new technologies. In order to grow, the fish-farming industry has to overcome significant challenges that require new innovations and technology. 194 Some of these are: dependence on marine feed resources, sea lice, diseases that contribute to a high average mortality rate, cost efficiency, product innovation to meet demand in old and new markets, and stricter government regulations. There have been a lot of R&D activities focused on these challenges, but the industry still finds it difficult to increase the production growth. 195 Some innovations have taken over for human labor, and made production more cost efficient, but researchers still struggle to reduce sea lice, escapes, disease and algal blooms. New innovations to battle with these challenges involve closed farms to prevent hazardous emissions from the cages, fighting with diseases such as sea lice and new types of feed that can replace the scarce resource of fish oil. 196 Recent breakthroughs have found a vaccine against Pancreas Disease (PD) which is expected to have a positive effect on supply, and cut the costs associated with vaccination in half, as well as reduce the stress the fish experiences in the farms. 197 As mentioned in section 4.1, LSG undertake own R&D projects in order to boost harvest volumes and productivity in their operations. Some of these are: advanced smolt facilities, infrastructure, and preline for post-smolt production. We expect that these investments will have a positive effect on LSG s harvest volumes in the future. 4.3.5 Environmental factors We will here look at factors that affects the salmon production once at sea. 193 Asche et al. (8/2011) En kunnskapsbasert sjømatnæring Handelshøyskolen BI pg. 122-124 194 Asche et al. (8/2011) En kunnskapsbasert sjømatnæring Handelshøyskolen BI pg. 126 195 CAGR of 6% over the last 5 years, compared to 8% the previous 5 years. 196 Forskning.no (05.12.2013) «Forbedring eller død for fiskeoppdrett» 197 Laks (02.03.2015) «Etterlengtet laksevaksine fra Bergen» 67

Sea temperature Graph 4.4: Sea temperature Source: MHG handbook 2014 Sea temperature is the main environmental factor for determining the fish growth rate and a temperature between 8-14ºC, as illustrated by the shaded area on the graph, is optimal for growth. 198 A temperature below 8ºC will increase the feed required to grow, while a temperature above 14ºC will give the salmon lower appetite which leads to lower feed intake and slower growth. 199 From the graph above, we see that Chile and Canada have better sea temperature conditions than the European countries. This gives them an advantage in form of a shorter production cycle, increased production and lower costs, as the added production time incurs higher variable costs. The Norwegian sea temperature has in the period 1980-2008 increase by 1.27ºC in the northern parts, while the southern part has increased by 1.68ºC. This climatic change has helped to boost Norway s supply of salmon, but the effect is declining. Researchers expect Norway to see a modest increase in sea temperature over the next decade due to global warming. This increase will still be within the biological sustainable limits of the fish. The risk exposure is however expected to increase since the increased sea temperature will increase the frequency of algae blooms and concentrations of bacteria. 200 Diseases Salmon diseases was first discovered in the early 80 s, and as such, has followed the industry through its development and have impacted the global supply. 201 These diseases have threatened the industry's existence through economic losses following a period of significant reductions in production and destruction of infected fish. Some vaccines have been developed to mitigate diseases, but disease outbreaks still cost the industry large sums in form of high mortality rates and disease control. Proper 198 Marine Harvest Handbook (2014) pg. 32 199 Sysla (29.07.2014) «Gir råd om fôring av laks i varmen» 200 Lorentzen, Torbjørn (klima 2. 2010) «Økt sjøtemperatur påvirker lakseoppdretten» pg. 2-3 201 Asche et al. (2010) The Salmon disease crisis in Chile pg. 3 68

distance to other salmon farms and destruction of infected fish has been the best solution until new or better vaccines occurs. 202 Pancreases Disease (PD) is the most common disease and it was reported 137 PD cases in 2012, 100 in 2013 and 142 in 2014. 203 The mortality rate of PD is varying - usually between 5-10% of the fish dies, but the mortality can also increase to 80% in exceptional cases. 204 The new PD vaccine mentioned in section 4.3.4 (pg. 67) is expected to reduce the PD outbreaks significantly in the future. Another dangerous disease is the infectious salmon anemia (ISA) which increased from 2 outbreaks in 2012 to 9 outbreaks in 2013. 205 This development is related to the increased water temperature discussed earlier. The ISA outbreaks in 2003 in Faroe Island and 2009 in Chile are the two most serious in terms of relative terms and production losses. The Faroe Islands reduced their production to one fifth of what it was at its peak and Chile reduced their production with more than 50%. 206 The decrease in production in Chile led to a negative growth in supply in 2009 and 2010, which again led to a high price of salmon these years. 207 Since these outbreaks often affect whole regions, it is strategically advantageous to be geographically diversified in the production phase. Although fish farming is still a young industry, with regards to infectious salmonid diseases, there has been a stabilization of mortality in Norway due to good husbandry, management practices and vaccination. Chile has also shown a positive development after rebuilding the industry following the ISA outbreak in 2009-2010. 208 On behalf of this, and previously discussed measures taken by LSG and the peer group, we expect diseases to have a less negative impact on supply and growth in the years to come. 4.4 Salmon price As discussed throughout the thesis, LSG s operating revenues and performance are affected by the volatility in the salmon prices. The price of salmon is heavily dependent on changes in supply and demand and as seen from the graph underneath, variations can be large and rapid. The reason for this is that salmon companies have very limited flexibility to control supply in the short term, as the production cycle 202 Asche, et al. (04.11.2011) Future challenges for maturing Norwegian salmon aquaculture industry pg. 45 203 http://www.vetinst.no/temasider/fisk/pankreassykdom-pd - Norwegian Veterinary Institute 204 http://www.vetinst.no/temasider/fisk/pankreassykdom-pd - Norwegian Veterinary Institute 205 http://www.vetinst.no/nor/temasider/fisk/infeksioes-lakseanemi-ila - ISA outbreaks in Norway 206 Asche et al. (2010) The Salmon disease crisis in Chile pg. 4-5 207 Average spot price for salmon was 30.9 in 2009 and 37,3 in 2010. 208 Marine Harvest Handbook (2014) pg. 60 69

lasts for about three years. 209 Furthermore demand is seasonal. 210 This causes miss matches in the market as salmon is mostly sold as fresh product, and leads to high volatility in the spot price. Graph 4.5: Salmon price development 2006-2015 Source: Authors creation, yahoo finance The graph above is collected from Fish Pool Index (FPI), and is based on a weighted weekly average of sizes 3-6 kg, superior quality head-on gutted salmon. 211 The salmon price has gone from 24.71 NOK/kg in the start of 2006 to 37.06 NOK/kg in week 16 of 2015. The average spot price in the period has been 32.64 NOK/kg. The salmon price has in recent years been a lot higher than the average. This has been a result of an increasing annual growth rate in demand surpassing a diminished growth rate in supply. 212 In order to explain the volatility in the salmon price, and to put us in a position that enables us to forecast the future price, we will look further into factors that affect the supply and demand in the coming sections. 4.4.1 Supply Historically, the growth in global supply has been the main driver behind the volatility in salmon prices. Graph 4.6: Change in price and supply Source: Authors creation, MHG handbook 2014 209 Marine Harvest Handbook (2014) pg. 29 210 Marine Harvest Handbook (2014) pg. 24 211 www.fishpool.eu Spot-prices 212 Marine Harvest Handbook (2014) pg. 17-18 70

The graph above shows a linear correlation between the change in global supply and change in the FHL (Fishpool) price from Norway. The correlation have an explanatory power of 57% of the annual price development between 2000-mid june 2014, the same explanatory power was 87% between 2000 and 2011. 213 The recent decline in explanatory power is mainly due to the significant over-performance of demand in 2012, 2013 and first half of 2014 as pointed out in the graph. The fluctations in global supply can be explained by the profitability cycle in the industry - where fish farmers have released more smolt when the prices are high, and less when the prices are low. Changes in biomass, smolt release, disease outbreaks and sea tempature are important indicators of future supply. 214 The supply of salmon has since 1994 increased by 428% with an CAGR of 9%. The period 2004-2014 had a lower CAGR of 6%, with supply varying between -2% and 22%. 215 Global salmon supply - 2012-2017E 1000 tonnes WFE 2012 2013 2014E 2015E 2016E 2017E Norway 1183 1144 1198 1266 1294 1357 Others 248 244 268 261 276 290 Europe 1431 1388 1466 1527 1570 1647 Annual growth 16 % -3 % 6 % 4 % 3 % 5 % Chile 364 470 583 576 632 632 Others 209 193 188 221 225 228 Total other 573 663 771 797 857 860 Annual growth 48 % 16 % 16 % 3 % 8 % 0 % Total global supply 2004 2051 2237 2324 2427 2507 supply growth 24 % 2,3 % 9,1 % 3,9 % 4,4 % 3,3 % Source: compiled by authors', Kontali analyse, Nordea markets Annual average prices have as a consequence varied between 19.5 NOK (2003) and 38.97 NOK (2013). 216. Nordea Markets has together with Kontali estimated the following development in supply growth: 217 The reason for the diminishing CAGR is that the industry has reached production levels where biological boundaries are being pushed. It is therefore expected that future growth cannot be driven by industry decisions alone, but will come as a product of technological innovation, development of improved pharmaceutical products, implementation of non-pharameceutical techniques, intercompany cooperation, and improved industry regulations. 218 Some of these have been discussed above, and it is clear that the industry is working on means to better efficiency in the production phase, as well as improving disease control. Table 4.4: Global supply 2012-2017E 213 Marine Harvest Handbook (2014) pg. 23 214 Marine Harvest Handbook (2014) pg. 62 215 Marine Harvest Handbook (2014) pg. 18 216 Marine Harvest Handbook (2014) pg. 23 217 Nordea Markets - Sector Seafood Update (25.03.2015) pg. 20 218 Marine Harvest Handbook (2014) pg. 18 71

The most important indicators for future harvest quantities will be analyzed in the next sections with the aim to help us forecast future supply in the forecast section of our thesis. 4.4.2 Biomass, feed sales and smolt release Along with the already discussed factors; seawater temperature, 219 disease outbreaks 220 and vaccines; 221 standing biomass, feed sales and smolt release are the best indicators for future short and medium-term harvested quantities. Standing biomass Graph 4.7: standing biomass Source: Authors creation, Fiskeridirektoratet The best short term indicator for harvest volume is standing biomass categorized by size above 4kg. 222 Graph 4.7 shows the annual development of the standing biomass in Norway from 2005 to April 2015. 223 The annual changes have been varying. The largest growth was 16% (2006 to 2007) and the smallest growth was -0.7% (2012 to 2013). The impressive growth in 2007 was related to optimal sea water temperature and the decrease in 2013 is related to diseases. 224 Both of these annual changes can partly be seen in relationship with the salmon price in graph 4.9 where an increase in supply decreased the salmon price and conversely. The declining trend from 2009 is a result of companies reaching maximum capacity utilization. 225 219 See section 4.3.5 220 See section 4.3.5 221 See section 4.3.4 222 Marine Harvest Handbook (2014) pg. 62 223 Fiskeridirektoratet (15.04.2015) «Biomassestatistikk» 224 NRK (04.01.2013) «Laksesykdom ute av kontroll» & Fiskeri- og havbrusnæringens landsforening AR (2009) pg. 39 225 See section 4.1 - Some companies are above the theoretical limit when it comes to yield per license. 72

Looking at the future supply, the standing biomass has increased with 3.5% in the three first months of 2015. This is a result of higher-than-normal water temperature going into 2015. 226 This growth rate is in line with the declining growth in standing biomass and Nordea s forecast. Unless the government issues new licenses, then it is expected that the growth in standing biomass will come from operational improvements and the new traffic light system. Smolt release and production Graph 4.8: Smolt release Source: Authors creation, Fiskeridirektoratet As discussed in section 2.2.4 (pg. 15), it currently takes 18-22 months from smolt are released until they are ready to be slaughtered. Smolt released in 2013 and 2014 will therefore have an effect on harvest volumes in 2015 and 2016. The growth in smolt release was 7% and 4.2% in 2013 and 2014 respectively. This supports a diminishing growth rate in supply for the next two years. At the same time, new laws permitting land-based farming and post smolt facilities discussed in section 4.3.1 (pg. 62) is expected to have a positive effect on smolt production. The increased size of smolt and post-smolt will not lead to a huge shock effect on short term, but have the potential to gradually enable farmers to increase their volumes by 25-50% with the same license capacity. It is estimated that around 30% of the smolt in Norway over the next four years will be 250g or larger, meaning that it will not affect the supply before 2017, and at that time it will have the potential to add 5-7% annual supply growth from Norway. 227 226 FonsFinans Sector Report (10.04.2015) pg. 13 227 Nordea Markets - Sector Seafood Update (25.03.2015) pg. 19 73

Fish feed Graph 4.9: Fish feed Source: Authors creation, Fiskeridirektoratet The decrease in fish feed from 2012-2013 does not necessarily mean lower production growth in the future. The reason for the negative growth in 2013, and low growth in 2014 was mild winters and higher water temperature in 2013/2014 and 2014/2015 which gave the salmon better growing conditions and required less fish feed. 228 The fish feed moved back to normal annual growth rate in 2014 as a part of growing biomass, and indicates a growth in supply slightly below that in 2011 and 2012. 4.4.3 Lack of space Lack of space is currently a major limitation for future growth in supply. The fish farming industry was until the late 1990s increasing the number of cages in their facilities and adopting new spaces for production. There are two conditions which makes it hard for this trend to continue in Norway and other major salmon farming countries. 229 First off, the fish farming industry is continuously looking for so-called "super sites". These areas have sufficient depth, good water exchange, are reasonably sheltered from fierce winds and high waves and have access to good infrastructure on land in form of electricity, roads, water and jetty. Secondly, there are not many of these sites available and those that exist are requested by a number of industries along the coastal zone. The increased exploitation of these areas increases the chance for negative environmental impacts and creates further problems. 230 Therefore, an increase on the supply side is unlikely to come from new sites, and efficiency in production again seems like the best option to boost supply growth in the future. 228 Nordea seafood sector update (25.03.2015) pg. 21 229 Forskning.no (05.12.2013) «Forbedring eller død for fiskeoppdrett» 230 Aftenposten (20.09.2013) «Kampen om kysten» 74

4.4.4 Demand The demand for salmon has the last ten years had an annual growth rate of 11%, which is substantially higher than the 6% growth rate in supply. This difference explains some of the historically raising prices and is thus useful when predicting future prices. 231 Pareto forecasts a stable annual demand growth for Norwegian products between 8-10% from 2015 to 2025. 232 However, the short term demand will be characterized by volatility due to Russian and Chinese import bans, and currency issues discussed in the PESTEL analysis above. We will now discuss different factors affecting future demand. Population growth, changes and new markets Globally speaking Asia and Africa will have the highest population growth in the years to come, but the salmon price in these regions is generally high and the consumption has therefore been low. 233 With the expected high level of the salmon price, it will not be an attractive alternative for most countries in these continents, as other protein sources are available at much lower prices, as discussed in section 4.2.4 (pg. 59). One example of the high salmon price affecting demand is France, which traditionally have been one of the largest salmon markets in the world and among Norway s top-three markets. France have in recent years declined their imports from Norway as a result of new and higher prices for its low-end segment as well as negative TV campaigns. 234 The France low-end segment has thus moved towards cheaper substitutes. Greater prosperity in emerging markets will however help to keep a high future annual growth in demand. The value of the Norwegian exports towards the BRIC countries have tripled in the last decade and the export is expected to grow even more as the global middleclass is forecasted to increase from 2 billion to 4.9 billion in 2030. 235 Even though the BRIC countries have shown short-term weakness due to sanctions (Russia and China) and weakened currencies (BRL and RUB), it is still expected that these countries will affect the long term demand positively. To clarify the potential, appendix 4.3 shows that it is currently consumed less than 1 kilogram yearly per capita in the BRIC countries compared to 6-8kg in Scandinavia. 231 Guttromsen. Hva påvirker laksepriser Handelshøyskolen ved UMB 232 Pareto equity research seafood (10.04.2015), pg. 1 233 United Nations (13.06.2013) World population projected to reach 9.6 billion by 2050 234 Nordea Markets - Sector Seafood Update (25.03.2015) pg. 17 235 OECD Observer (2012) An emerging middle class 75

Product innovation Product innovation is important for future growth and maintaining and developing the customer base. As mentioned in section 2.4 (pg. 20), LSG believes that product development is a key factor for sustaining growth in demand. An example of this is Germany where the major discount retailers have 50% market share, and thanks to their highly successful introduction of fresh fillet packages, salmon consumption is increasing. The import of Norwegian salmon to Germany is expected to increase with 15% in 2015, but smoked and frozen salmon is declining, meaning that fresh salmon has cannibalized on the other categories. 236 This is related to the sushi trend which has expanded enormously in recent years and which has gone from gourmet food towards volume production. This is something that has increased the demand for fresh salmon and something that LSG have benefitted from as Norway s largest supplier of sushi. 237 4.4.6 Summary supply and demand The above analysis have revealed that the short term supply will have diminishing growth due to the Norwegian salmon farmers approaching the capacity ceiling for MAB. There has also been lower growth in biomass and diminishing growth in smolt release. The medium- and long-term supply will be dependent on the new traffic light system, which is expected to yield an annual growth rate in supply of approx. 3% from 2017/2018. In addition, investments in R&D and opportunities for larger smolt and post-smolt production will have a positive effect on supply in the medium and long term. All in all, the annual growth rate in supply is expected to be around 3-4% in short term, while the medium- and long term growth is expected to be 4-6%. The demand for salmon has been high and steady in recent years. This trend is expected to continue as a result of population growth, increasing middle class, product innovation, health focus and the expectations of a weakened NOK. The growth in demand is expected to be weakened in the BRIC countries on short term, but pick up in the medium to long term. Poland, Germany, UK and Spain are continuing to show healthy growth rates, and are drivers behind an expected high and stable demand in Europe. 238 The shortand long term annual growth rate in demand is therefore expected to be steady at around 6-9% towards 2025. 236 Nordea Markets - Sector Seafood Update (25.03.2015) pg. 18 237 Lerøy Seafood - Annual Report (2014) pg. 5 238 See appendix 4.2 76

The diminishing growth in supply in the short term combined with a high demand growth means that the supply is not sufficient to meet the demand. We expect this to have a positive effect on the salmon price in the short- and beginning of medium term. However, as supply picks up in the medium- and long term, we expect the salmon price to start dropping and reach a sustainable level. 4.5 Connecting the analyses SWOT Below we will summarize our findings from the financial and strategic analysis in a SWOT matrix. Table 4.5: SWOT Spot & sales price Harvest volumes Cost drivers Strengths S - Highest premium in the industry - High entry barriers - Product development - First ASC certified fish-farmer - Strategic partnership with key distributors - Limited supply growth - Economics of scale - Technological advances made for production of big smolt and post smolt - Financially healthy, can undertake investments - Strategic partnership with key suppliers - Fully integrated company - High degree of automatization Weaknesses W - Fresh product, cannot time supply to meet demand - Expensive compared to other protein sources - Cyclical industry - Dependent on the underlying spot price of salmon - Long production cycle - Limited number of licenses issued - Limited growth opportunities - Low capacity utilization - Feed suppliers have high bargaining power - Historically the least costefficient producer - High salaries in Norway Opportunities O - Growing demand for salmon and VAP products - Growing demand for high EBIT products in Asia and possibly Europe - Growing population and protein demand - New traffic light system, MAB expected to grow - New acquisitions still not 100% integrated and efficient - New investments expected to increase capacity utilization - Investments made to better disease control - New vaccines in the market Threats T - Trade restrictions in historically large markets - Chilean production can be larger than expected - Environmental and biological risks may increase with global warming -Stricter regulations - Feed prices can go up as a result of suppliers power to transfer costs on raw materials on to salmon producers Overall assessment ST: Spot price expected to remain high as a function of high demand and low supply growth MT: Spot prices will fall slightly as supply catch up with demand LT: Stabilized demand and supply growth, spot prices expected to stabilize at a high level. ST: Long production cycles, strict regulations will keep supply growth low. MT: Supply growth higher as a result of higher MAB and post smolt. LT: Stabilized growth in harvest volumes as efficiency and MAB reaches a new sustainable level. ST: Efficiency gains from new investments, and economies of scale. MT: Feed costs expected to decline, more efficiency gains from investments. LT: Reach a level where costs are predictable and stable. Source: Authors creation 77

5. Forecasting Before we start with our forecast, we have to determine how long our forecast period should be and how detailed we should make our pro forma income statement and balance sheet. When deciding the length of our forecast period, it is important to estimate how long it will take before the company reaches steadystate performance. 239 As we will assume perpetuity growth after the terminal year, too short of a forecast period can lead to a significant undervaluation of the company, and a too long forecast period introduces extreme difficulties with forecasting individual line items 10-15 years into the future. 240 We have decided to forecast the income statement and balance sheet six years into the future, while the 7 th year will be our terminal period. This is because LSG and the industry have undertaken several new investments 241 which we estimate will contribute to continuous improvements in efficiency over the next six years. Furthermore, the new white paper discussed in section 4.3.1 (pg. 62) will affect efficiency these years. We estimate that these factors will lead to a new efficiency cap of 1400 tonnes per license in 2020. Furthermore, we will split our forecast into three parts: short-term, medium-term and long-term, where short-term will be the first two years of our forecast, medium-term will be the next four years, and finally long-term will be the final and terminal year in our forecast. 5.1 Income statement We will begin our forecast by forecasting the entire income statement. First we will estimate the future revenues. We have decided to use a production based approach to forecast operating revenue, as our analyses this far has shown that revenue is dependent on several key factors: Salmon price, harvest volume and sales premium, where the salmon price and premium are calculated as per kg estimates. In order to get a best possible estimation for these input factors, we will base our forecast on our previous analyses, as well as new analyses in order to derive future estimations. 239 Koller et al (2010) Valuation pg. 181 240 Koller et al (2010) Valuation pg. 181 241 See section 4.1, 4.2, 4.3 78

5.1.1 Salmon price forecast Our previous analyses 242 revealed that LSG s performance is highly correlated with the development in the salmon price. It is thus of upmost importance that we estimate a realistic salmon price throughout our forecast period. In order to derive best estimates, we have performed two regression analyses to identify the relationship between price, supply and demand. We have also collected information from market participants, investment banks and fishpool. As pointed out in our strategic analysis, supply and demand are the two factors that most affect the salmon price, we have therefore decided to run regressions with these two as the explanatory variables in our regression analyses. In our first regression we decided to use development in the EU GDP as a proxy for demand. This is because the EU is the biggest market for salmon, and demand in this region will be affected greatly by economic conditions i.e. GDP growth should be associated with a growth in demand. The outcome and analysis of this regression have been put in appendix 5.1, as the results lead to continuously rising prices in the future, which we deem highly unrealistic considering the historical development. In the second regression analysis, we use estimated demand collected from various sources as the proxy for actual historic demand, and estimations based on market consensus about future demand as a proxy for actual demand in the future. This regression analysis estimated what we believe is more realistic salmon prices for our forecast period, and we will explain the model in detail below. Regression analysis with supply and demand as explanatory variables As mentioned above, we used historical demand collected from credible sources as a proxy for actual demand. 243 This enabled us to run a multiple linear regression with numbers from 2002-2014. We have used change in salmon price as the dependent variable, and change in global supply and global demand as independent variables. The input data for the regression can be found in appendix 5.2, and the results are summarized in table 5.1. 242 Se section 2.9 (pg. 27), 3.3.1 (pg. 36) 243 Guttromsen,(03.07.14) «Økt etterspørsel. Produksjonsvekst i Norge?» / Guttromsen. Atle G. Hva påvirker laksepriser Handelshøyskolen ved UMB / Norwegian Seafood Council Megatrends seafood and impact on prices / FondsFinans - Aquaculture Sector Report (10.04.2015) 79

Regression analysis results Table 5.1: Supply and demand regression output R-Square 0,69 Variable Coefficient P-value Intercept 0,027 0,787 Global supply -1,766 0,023 Global Demand 1,333 0,052 Source: Authors' creation, MH handbook The explanatory power of the regression model, R square, indicates that 69% of the variation in the salmon price can be explained by the variation in supply and demand. The estimated parameters are also in line with our expectations; specifically an increase of 1% in supply is associated with a decrease of 1.77% in the salmon price. An increase of 1% in demand is associated with an increase of 1.33% in the salmon price. Both of the estimated parameters are statistically significant at the 10% level, but global demand is slightly over the 5% significance level. This suggests that there is a linear relationship between the change in salmon price, and changes in global supply and demand. The intercept of 0.026 tells us that if there is no change in supply or demand, the price will rise by 2.7%, suggesting that supply has a stronger effect on the price than demand. However the P- value of 0.79 means that this parameter is insignificant at any level. The following function can be derived from the output of the regression, and will be used to calculate our forecasted salmon price: Using this equation and our estimated future global demand and supply, discussed in section 4.4.6 and found in appendix 5.3, we get the following results for change in salmon price and salmon price in our forecast period. Hostoric Short term Medium term Long term Forecasted salmon price 2 014 2015E 2016E 2017E 2018E 2019E 2020E 2021E Supply growth 9,0 % 4,0 % 4,0 % 4,0 % 6,0 % 6,0 % 6,0 % 6,0 % Demand growth 8,3 % 5,0 % 7,5 % 6,0 % 6,0 % 6,0 % 6,0 % 6,0 % Salmon price growth 1,8 % 2,3 % 5,6 % 3,6 % 0,1 % 0,1 % 0,1 % 0,1 % Salmon price 41,2 43,5 45,1 45,2 45,2 45,2 45,3 Source: Compiled by authors' Our model shows an increasing salmon price throughout the forecast period. This is a result of global demand growth surpassing supply growth in the first three years of our forecast, and in these years the price will rise from its current level of 40.3 to 45.1. After 2018, global supply and demand growth are expected to be at the same level, and our model predicts that the salmon price will increase at a very slow rate until it reaches 45.3 in our terminal period. Table 5.2: Δsalmon price and estimated future price 80

Discussion of regression model The model above fits reasonably well with our findings in the strategic analysis, where we expected the price to rise in the short to medium-term as a result of stagnant supply growth and increasing demand growth. We did however expect the price to revert back to a normal level, as supply is expected to catch up with demand growth in the medium to long-term. Here our model estimates a slightly increasing price, as a result of the intercept being positive and countering the effects of the supply growth coefficient being higher, in absolute value, than the demand growth coefficient. The validity of our regression can be discussed further. We only have 13 observations, which is very low if you want to find a valid statistical relationship between variables. Furthermore, our estimates for historical demand growth are collected from various sources, which in some years has been slightly different. Nevertheless, we find most of our sources to be trustworthy, as they work within the field, and have published several articles in international acclaimed papers. 244 Our model also fails to take other factors that might influence the salmon price into consideration. It is highly likely that other factors such as: prices on substitute products, quality, diseases, food scares, and currency developments will affect the future price of salmon. Despite these critical arguments against our model, we have decided to include it in our forecast. This is because there is no other way of obtaining data sets with more precise estimations, our estimates are collected from trustworthy sources, estimating other effects and including it in our analysis is beyond the scope of this thesis, 245 and our estimates for the future price fits the earlier discussion and market consensus relatively well. Forecasted salmon price based on strategic analysis In this section we will estimate future salmon prices based on our findings in the strategic analysis, market trends and development, and future expectations. We will then compare our findings with market analyst and fishpool forward rates in order to obtain realistic salmon prices. Short term (2015-2016) In section 4.4 we found that the strengthened demand in the market pushed the salmon prices to new heights in 2013 and 2014. Further we found evidence that demand growth will continue to be strong in the 244 Asche - Employee at Universitetet I Stavanger Link to CV in reference list 245 We are performing a valuation, not an econometrical dissertation 81

short term. 246 In section 4.4.1 (pg. 71) and 2.2.3 (pg. 14) we found that stricter rules and regulations being enforced by governments, combined with few licenses being issued, means small growth opportunities for salmon farming companies in the short run. We therefore expect an increase in the salmon price the first two years of our analysis, and estimate a salmon price around 41 in 2015 and 43 in 2016. Medium-term (2017-2020) In the medium-term, new technologies and opportunities for increased biomass, large smolt and postsmolt discussed in section 4.3 (pg. 62) and 4.4.2 (pg. 73) will lead to higher supply growth from the middle of the period. The first year we expect supply conditions and growth to be similar to that in the short-term, as it takes time for new technology to be efficient plus delayed effect of the new traffic light system discussed in section 4.3.1 (pg. 62). Demand growth is expected to decrease slightly going into the period, and then remain stable throughout the period, as discussed in section 4.4.4 (pg. 74). We therefore estimate that the price will remain stable in 2017, and then start declining to sub 40 levels in 2018 and 2019, before it stabilizes in 2020. Long term (2021 onwards) The high volatility of the historical salmon price, makes forecasting the long term price a difficult task. We expect the prices to revert back and approach historical averages and stabilize, but at a higher level than the historic average of 32.6 247 would predict. This is a result of the recent development in salmon prices, discussed in section 2.2.6 (pg. 18), and that the industry and market seems to be more stable going forward. 248 A forecasted salmon price around 35-36 therefore seems reasonable. 5.1.2 Summary and conclusion salmon price Table 5.3 presents our final estimates together with the estimates from our regression model, fishpool forward prices and an average among eight investment banks. 249 Our estimates from the regression analysis seem to be too optimistic compared to our estimates based on the strategic analysis, as well as compared to market analysts and fish pool forward prices, especially from 2017 and forward. We have therefore adjusted all our regression estimates downward. Table 5.3: forecasted salmon prices Short term Medium term Long term Forecasted salmon price 2015E 2016E 2017E 2018E 2019E 2020E 2021E Regression estimates 41,2 43,5 45,1 45,2 45,2 45,2 45,3 Fish pool forward price 41,5 42,9 41,5 35,6 35,6 35,6 - Analysts average 40,9 42,8 42,1 Our estimates 41,0 43,0 42,5 38,0 36,0 35,6 35,6 Source: Compiled by authors', Nordea markets, Pareto, Fondsfinans, ABG sundal collier, SEB, Handelsbanken, Norne, Swedbank, Fishpool 246 See section 4.4.5 (pg. 76) 247 Calculated from 2006 to week 16, 2105. See section 4.4. 248 Pareto - equity research rapport seafood (10.04.2015) pg. 3. Also discussed in section 4.4. 249 See appendix 5.4 for complete list of investment banks and their price estimates 82

Compared to analysts our estimates are similar to the most positive investments banks, as we feel the strong demand will continue into the future, and keep the price high from 2015 to 2017. Compare to fishpool forward prices our estimates starts out lower, and then surpasses their forward prices from 2016-2019. This is because we concluded that the high demand will be sustained in the period, and the effects of supply growth will not hit the market fully before 2018-2019. In 2020 we expect the price to be equal of that of fishpool s forward price, as all effects from our strategic analysis will be accounted for. Overall, the average price in our forecast period is 38.8 NOK/kg. This is an increase of 19% compared to historical averages. This is a significant increase, but we feel it is sustainable based on our findings in section 4.4 and above. Especially when you compare the price development of salmon compared to substitute products, which historically have increased at rapid rates compared to salmon. Furthermore, the salmon market is maturing and expected to become more stable going forward, as mentioned in section 2.2.6 (pg. 18). The industry has thus reached a point where there s more predictability in prices, and both demand and supply exhibit stability at a level that supports higher prices. Based on these arguments, we find our estimated prices to be realistic over the forecast period. 5.1.3 Forecasted harvest volumes The next step will be to forecast future harvest volumes for LSG. As pointed out in our strategic analysis standing biomass, licenses and capacity utilization are the key drivers behind production growth. In order to estimate good future harvest volumes, we will base our forecast on findings from the strategic analysis, together with LSG s own estimates. Demand will be increasing throughout our forecasted period, and will thus not affect our forecast of harvest volumes. We expect LSG and its peers to produce at full capacity throughout the period. The demand will therefore only affect the salmon price, and not the supply. LSG s harvest volume has grown by an average of 8.1% over the last 5 years, slightly over the industry average. 250 Throughout the period LSG have acquired new licenses through M&A and purchases in the second hand market, in order to boost their harvest volume. Growth has also been a result of more efficient production and yield per license. We assume that these factors will be drivers behind future growth for LSG. We will not model unexpected environmental conditions like low water temperatures, outbreak of diseases etc. as the timing and magnitude of such events are close to impossible to estimate. 250 See appendix 5.6 83

Short term (2015-2016) In the first year of our forecast, we will use LSG guidance from 2014 as a starting point to derive our estimated harvest volume. Historically the group has estimated their future harvest volume with decent precision. In table 5.4, you can find their estimated forecasts and their actual forecasts over the last six years. Table 5.4: Expected vs actual harvest volumes, LSG Board guidance 2009 2010 2011 2102 2013 2014 Average Expected harvest volume 110 000 116 000 144 000 142 000 154 000 157 000 Actual harvest voume 108 500 116 800 136 600 153 400 144 800 158 300 Difference -1,4 % 0,7 % -5,1 % 8,0 % -6,0 % 0,8 % -0,5 % Source: Compiled by authors', LSG annual reports 2008-2014 The average difference over the period is -0.5%. The big outliers (2011-2013) came in periods with changing conditions and problems with diseases. 251 We therefore deem the managements estimations as good, and will set the harvest volume to 166 000 GWT, as per their guidance. 252 The increase in volume is estimated at 4.9%, as a result of fully consolidating Villa organic, 253 and more efficient production in existing productions. In 2016, we expect that 3 licenses acquired in 2014 will start having an effect on harvest volumes. Also licenses obtained following their consolidation of villa organic is expected to be fully utilized at this time. Furthermore, we estimate that the investments discussed in section 4.1 will affect efficiency and raise the yield per license to a higher level. Taking all of this into consideration we estimate a growth rate that is significantly higher than the expected growth rate for the Norwegian supply in 2016. 254 We have thus forecasted a harvest volume of 175 960 tonnes, a growth rate of 6%, in 2016. Medium term (2017-2020) In the medium term, we expect the growth in harvest volume to vary over the period. As mentioned in section 2.2.3 (pg. 15), we do not expect large salmon companies like LSG to be issued new licenses by the government, and buying licenses in the second hand market or acquiring smaller companies is likely the only solution to expand operations. Taking historical development, the raised ownership limitation 255 and LSG s upstream and downstream M&A strategy 256 in to consideration, it is likely that LSG will continue their M&A activities in this period. However, it is hard to predict which companies they will target for takeovers, 251 See section 3.3.2 (pg. 38) 252 Lerøy Seafood - Annual Report (2014) pg. 16 253 Villa organic was consolidated from 1.07.2014, and 6 000 tonnes was thus not accounted for in the 2014 AR 254 Expected supply growth in Norway in 2016 is 2.2%, as seen in table 4.4 255 Maximum ownership in a region was raised from 25% to 40% 256 Lerøy Seafood - Annual Report (2014) pg. 11 84

and when eventual takeovers will occur. We have therefore chosen not to forecast eventual take overs in the period, but expect them to obtain licenses throughout the period, in order to boost harvest volumes. The new traffic light system, discussed in section 4.3.1 (pg. 62), will start to show effects in late 2017/2018. We expect that new technology put in place by the group in 2014 and 2015, and their continued work with disease control, will put them in a position to take advantage of this new system, thus increasing harvest volumes in some regions. Higher biomass allowed combined with larger smolt from smolt and post-smolt production, will increase LSG s yield per license considerably in the period. We expect this growth to be gradual, and that they will reach a new efficiency level of 1400 by the end of the period. Based on these arguments we expect a growth rate of 7% in 2017 here some of the growth will come from licenses acquired in 2014 and 2015 as well. In 2018 we estimate a growth rate of 5%, while we expect the growth to stabilize at 4% for the rest of the period. Long term (2021 onwards) In the long term, we set the growth rate in harvest volumes to 2.5%, equal to the target inflation rate set by Norges Bank 257. Our harvest volumes estimates for the entire forecast period are summarized below. Table 5.5: Forecasted harvest volumes Forecasted harvest volumes, LSG 2015E 2016E 2017E 2018E 2019E 2020E 2021T Licenses 142 142 145 146 150 153 Yield per licens 1169 1 235 1300 1350 1375 1400 Harvest volume 166 000 175 960 188 277 197 691 205 599 213 823 219 168 Growth 4,9 % 6,0 % 7,0 % 5,0 % 4,0 % 4,0 % 2,5 % Source: Compiled by authors', LSG annual report 2014. 5.1.4 Sales premium Section 4.1 (pg. 51-53) revealed that LSG s main competitive advantages are their worldwide sales and distribution network and product innovation, which leads to a high sales premium on their products. This is advantages we expect LSG to uphold in the future, and it is a key value driver for the company. It is therefore important that we estimate future premium as precise as possible, in order to forecast realistic revenues. In appendix 5.10, you can find LSG s historical sales premium from 2005-2014. The average sales premium has on average been 2.04 the last five years. There was a rising trend from 2010-2012, before it dropped in 257 www.norges-bank.no/en/statistics/inflation/ - Inflation 85

2013 a result of a higher spot price, and lower growth in achieved price. In 2014, when the price was stable, the premium approached 2. Digging deeper into the numbers, we find that the spot price influences the premium negatively. 258 Since we have already estimated future spot price, we will use this relationship in our forecast period to obtain as precise a sales premium as possible. As per LSG s strategy, and our findings in section 4.1.1 (pg. 54) we assume that they will continue their product innovation and strong focus on VAP throughout the period. Short term (2015-2016) We earlier estimated that the spot price will be rising in this period. We therefore find it likely that the sales premium will drop, and be below the five year average. In 2015, the increase in price will be small and we thus estimate the sales premium to be relatively stable, and estimate it to be 1.95. In 2016, we estimated that the price will reach its top, and thus estimate a lower sales premium of 1.85. This is well below average, but with an all-time high price this year, we find it reasonable that the sales premium will be slightly below the historical lowest level (1.88). Medium and long-term (2017-2021) In the medium term, we expect the salmon price to decline and stabilize at a new level. As a result of the negative correlation, we estimate that the sales premium will rise toward the historic average before it stabilizes at 2. The estimation is 1.88 and 1.95 in 2017 and 2018 respectively, and at 2 for the rest of the period. Below we have summarized our sales premium forecast, and calculated the correlation between salmon price and sales premium to ensure that our result is consistent with the historic development and our findings in the strategic analysis. Table 5.6: forecasted sales premium Forecasted sales premium 2015E 2016E 2017E 2018E 2019E 2020E 2021E Spot price 41 43 42,5 38 36 35,6 35,6 Sales premium 1,95 1,85 1,88 1,95 2,00 2,00 2,00 Correll -0,94 Source: Compiled by authors 5.1.5 Summary revenue forecast Combining all our previous forecasts, leads to the following operating revenue forecasts: Table 5.7: forecasted operating revenues Forecsted operating revenue 2015E 2016E 2017E 2018E 2019E 2020E 2021E Harvest volume 166 000 180 940 191 796 201 386 209 442 217 819 223 265 Price 41,0 43,0 42,5 38,0 36,0 35,6 35,6 Premium 1,95 1,87 1,85 1,95 2,00 2,00 2,00 Sales price 80,0 80,4 78,6 74,1 72,0 71,2 71,2 Operating revenue 13 271 700 14 549 385 15 079 992 14 922 719 15 079 800 15 508 737 15 896 455 Source: Authors' creation 258 The correlation between spot price and sales premium is -0.85 from 2006-2014, and -0.92 from 2010 to 2014, see appendix 5.5. 86

5.2 Forecasted operating costs To forecast future costs we will look at historic development of cost levels as a percentage of revenues, and combine this with our previous analyses in order to get the best possible estimates for future cost levels. We have also estimated costs on a production based level in order to further validate our forecast. Our estimates from the production based approached can be found in appendix 5.8 and 5.9. 5.2.1 Cost of goods sold Cost of goods sold has been relatively stable around 63-64% over the last five years, with the exception of 2012 where high feed costs combined with a low spot price greatly influenced COGS. 259 As discussed in section 3.3.2 (pg. 38-39) rising feed prices and problems with disease outbreaks has contributed to higher costs in recent years. Fish feed accounts for approximately 50% of COGS in the industry, and a rise in feed prices thus affects this line item greatly. As LSG strategy involves incurring higher COGS, feed prices will not affect 50% of their COGS, but is still an important contributor. In section 4.4.2 (pg. 57) we found that feed prices are expected to rise slightly in the start of 2015, before it drops in 2016 and stabilizes at a normal level. LSG have also made investments in order to combat disease outbreaks and problems with lice, which we expect will contribute to a decreased COGS over the period. As a result of slightly higher fish feed costs in 2015, we estimate a COGS of 64% of operating revenue, a 0.4% increase from 2014. In 2016, we estimate COGS to be 63.6% as a result of lower feed prices, and better disease control. The impact of disease control will be somewhat offset by costs incurred with a higher level of cleaner fish, as discussed in section 4.1.1 (pg. 54). In 2017, feed costs are estimated to have stabilized and as a result we estimate a 0.2% drop which is attributed to lower costs related to disease control. In 2018 and 2019 we estimate costs to drop further, as a result of investments undertaken to better disease control and efficiency in production. 260 We estimate that it will drop to 63.2% and stabilize at 63% from 2019 and onwards. To check the validity of our estimates, we have calculated costs per KG with these input factors. The costs per KG, reveals rising costs in 2015 (51.2), before it gradually drops down to 44.9 in 2020 and onwards. We find this a realistic COGS per kg, as it reflects lower feed costs, continued efficiency and better disease control. 259 Low of 63% (2013), High of 70.8% (2012) 260 See section 4.1 87

5.2.2 Salaries and other personnel costs Salaries and other personnel costs were increasing in the first three years of our analysis, and then it dropped in 2013, and remained stable in 2014 at 10.1%. The average over the 5 year period is 10.2% and we expect this to be a good indicator of the costs level for this line item in the future, as a result of measures taken by the industry discussed in section 3.3.2 (pg. 38). We therefore set salaries and other personnel costs to 10.2% of operating revenue throughout our forecast. 5.2.3 Other operating costs Other operating costs have been slightly increasing over the past five years, with an average of 9.2% of operating revenue. In 2014, the line item was 10%, up from 9.3% in 2013. We therefore find it reasonable to estimate it above the 5 year average, and estimate it to be 9.5% of operating revenue for the entire forecast period. 5.3 Other line items Income from associates have varied from 0.2% of operating revenue (2011) to 1.8% (2013), with an average of 0.9%. The reason for the high number in 2013 was that they bought shares in Villa organic and treated it like an associated company for 2013, before it was consolidated during 2014. We therefore adjust this number down to 0.4%, which is the average number for 2011, 2012 and 2014, for the entire forecast period, thus assuming that associated companies will follow LSG s development. Depreciation has over the period been stable around 13-15% of PPE, with an average of 13.9%. The line item was decreasing from 2011 to 2013, before it increased to 13.8% in 2014. This was a result of Villa organic being consolidated and other investments during 2014. We expect the 2014 level to be a good indication for future depreciation, and estimate it to be 13.8% of PPE throughout the period. We will not forecast other revenues, as this has been a result of gains related to sale of shares, gains associated with mergers, and gains on sold equipment. The line item has also only been present the last two years. The tax rate is sat equal to the current income tax for companies in Norway, 28%. The pre-tax borrowing cost will be set to 5.2%, in accordance with our calculation in section 6.3 (pg. 103), where we calculated the required rate of return on debt. In the same section we estimated LSG s future 88

capital structure as 80% equity and 20% NIBD, we have therefore set NIBD to 20% of invested capital throughout the period. 5.4 Summary Income statement forecast Our previous estimations lead to the following pro forma income statement: Table 5.8: Pro forma income statement 2015E 2016E 2017E 2018E 2019E 2020E 2021E Operating revenue 13 271 700 14 129 671 15 203 384 15 024 521 14 803 107 15 224 173 15 604 777 Total revenue 13 324 787 14 186 190 15 264 197 15 084 619 14 862 319 15 285 069 15 667 196 Operating costs Cost of materials -8 493 888-8 986 471-9 638 945-9 495 497-9 325 957-9 591 229-9 831 010 Salaries and other personnel costs -1 353 713-1 441 226-1 550 745-1 532 501-1 509 917-1 552 866-1 591 687 Other operating costs -1 260 812-1 342 319-1 444 321-1 427 329-1 406 295-1 446 296-1 482 454 Total operating costs -11 108 413-11 770 016-12 634 012-12 455 328-12 242 169-12 590 391-12 905 151 EBITDA 2 216 374 2 416 174 2 630 185 2 629 291 2 620 150 2 694 679 2 762 046 Depreciation -384 614-399 728-430 104-425 044-418 780-430 692-441 459 EBIT 1 831 760 2 016 445 2 200 082 2 204 247 2 201 370 2 263 987 2 320 586 Tax -512 893-564 605-616 023-617 189-616 384-633 916-649 764 NOPAT 1 318 867 1 451 841 1 584 059 1 587 058 1 584 986 1 630 070 1 670 822 Non-operating items Financial expenses -113 457-124 845-135 438-135 843-136 593-141 253-144 784 Tax shield financial expenses 31 768 34 957 37 923 38 036 38 246 39 551 40 540 Net financial expenses, after tax -81 689-89 889-97 515-97 807-98 347-101 702-104 245 Net profit 1 237 178 1 361 952 1 486 544 1 489 251 1 486 639 1 528 368 1 566 578 Source: Authors creation 5.5 Balance sheet forecast For our balance sheet forecast, we will mainly use a % of operating revenue approach. Alternatively we could set up the balance sheet using a production based approach. We chose the % of operating revenue approach, as it explained the development in balance sheet items better and was overall less volatile in historical perspective. When we deviate from this approach, we will explain in detail why we chose to do so. For some of the line items we have chosen to use aggregated value drivers. This is because some of the information and thus estimations becomes less accurate the longer the forecasting period extends. 261 Specifically, this applies to the calculation of NIBD, which we assume constant as 20% of invested capital throughout our forecast period, as estimated in section 6.1.1 (pg. 98). Our forecast assumption can be found in appendix 5.7. 261 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 186 89

5.4.1 Non-current assets Non-current assets consist of deferred tax assets, licenses and right, PPE, shares in associates, non-current receivables and goodwill. Deferred tax assets and non-current receivables have historically been very low at 0.16% of revenues on average over the past five years. Both have also been upward sloping, and we thus estimate them slightly above average, at 0.2% of operating revenue for the entire forecast period. Licenses and rights have historically been booked in the balance sheet as cost price less impairment costs. 262 To accurately measure this post, we will therefore estimate how much LSG need to invest in new licenses in every period of our forecast, and add this value to previous year s item. Under the revenue forecast earlier, we estimated growth in harvest volume. We will use these numbers, and expected yield per license to calculate how many licenses LSG will need to acquire each year. As discussed in section 2.2.3 (pg. 15), LSG s future increase in licenses will come from buying in the second hand market, M&A activities, and possible green licenses on tender. Because we will not estimate future M&A activities and issuance of green licenses are hard to predict, we look to the second hand market to estimate how much LSG will have to pay for each license in the future. From the last issue of normal licenses in 2009, the average second hand market price has been 33 million NOK per license. 263 Some of the license from this issuance has been sold for 50-60 million NOK. Because of the current high price on salmon, and developments in the market, we expect the price to be well above the average of 33 million. Furthermore, MHG industry handbook 2014 operates with an estimated cost per license of 40-60 million NOK, 264 and Pareto estimate a cost of 60 million per license after 2017. 265 We therefore find it reasonable to estimate a cost per license of 50 million NOK throughout the forecast period, 266 except for the 1 license attained in 2015, which was a green license that cost 10 million NOK. 267 Table 5.11 shows the resulting forecasted licenses and rights. 262 Lerøy Seafood - Annual Report (2014) pg. 72 263 Adressa (16.01.2014) De store kjøper laksekonsesjoner 264 Marine Harvest Handbook (2014) pg. 48 265 Pareto - Seafood Research Report (10.04.2015) pg. 39 266 LSG was offered a green license on tender for 10 million NOK in 2014, they have included this license from 2015, which is why the price differs this year. 267 http://www.hegnar.no/bors/artikkel509007.ece 90

Estimated investment in licenses 2015E 2016E 2017E 2018E 2019E 2020E Licenses and rights, Primo 2 151 685 2 161 685 2 185 572 2 303 116 2 383 576 2 538 001 Harvest volume 166 000 175 960 188 277 197 691 205 599 213 823 Yield per license 1169 1235 1300 1350 1375 1400 Estimated number of licenses 142 142 145 146 150 153 Licenses needed 1 0 2 2 3 3 Price per license 10 000 50 000 50 000 50 000 50 000 50 000 Investment in licenses 10 000 23 887 117 544 80 460 154 425 160 207 Licenses and rights, Ultimo 2 161 685 2 185 572 2 303 116 2 383 576 2 538 001 2 698 208 Source: authors' creation, adresseavisa, MH handbook 2014, Pareto Table 5.9: Forecasted licenses and rights Building, real estate and operating accessories have increased in absolute numbers throughout the period, as LSG have made continuous investments in order to become more efficient, and as a necessity to operate new licenses. In terms of % of operating revenue, the item was rising from 2010 to 2012, before it started dropping. This was because of large investments in smolt producing facilities in this period. 268 The average over the period was 20.9% of operating revenue. In 2014 the item amounted to 21.3% of revenues, and because LSG is now a fully integrated fish-farming company we think this is a good indication of the future level of PPE, as the company have not stated that they will undertake any big investments in the future but rather that they will assess potential investment opportunities individually as they come up. 269 We have therefore estimated Buildings, real estate and operating accessories to 21% in 2015, and 20.5% in the rest of the period. Shares in associates have been relatively stable over the period, except for 2013 when LSG bought 50% of Villa organic. Villa organic was consolidated as of 1.07.2014, and we therefore expect this item to drop back to the level it was before 2013, and estimate it to be 3.8% of operating revenues throughout the forecast period. Goodwill will be held constant at 2014 absolute number and will grow with the expected growth rate of 2.5% in the terminal period, as we have decided not to forecast any acquisitions in the period. 5.4.2 Current assets Current assets include biological assets, other inventories, trade receivables and other receivables. Biological assets represent the fair value of the fish in sea, adjusted for logistics costs and quality differences. Historically, this line item has varied from 25.8% of operating revenues (2011) to 34.6% of 268 Lerøy seafood annual report 269 Lerøy Seafood - Annual Report (2014) pg. 60 91

operating revenue (2013). The average over the period is 30%, whereas it was 29.3% in 2014. As this line item will be dependent on harvest volumes and maximum biomass allowed and salmon price, we estimate this line item to be increasing over time, until full efficiency and MBA is reached. In 2015 we expect it to be around 2014 levels and estimate it to 29.5% of operating revenues. We then expect it to grow steadily toward 31% in 2020, when we estimate that LSG will reach full capacity utilization and MBA. Other inventories, trade receivables and other receivables have been relatively stable around their respective averages, and we therefore set them equal to their averages throughout the forecast period. 5.4.3 Non-interest bearing debt (current liabilities) Trade payables have been varying between 7.2% and 9.8% of revenues. The 5 year average is 8.4%, and this was also the number in 2014, we therefore estimate it to be 8.4% of revenues throughout our forecast period. Public duties payables, taxes payable and other current liabilities are line items that have been relatively stable and small over the period, and we have thus set them equal to their five year average. Deferred tax liabilities is a line item that can be forecasted a number of ways. One can estimate changes for every year of the forecast, leave it at the same level throughout the forecast period, or eliminate it in the first year of your forecast. It is hard to predict when, if ever, deferred tax liabilities will be paid. It can be an ongoing line item with increasing size if the company continues investing in future periods. 270 The only thing that is clear about deferred tax liabilities is that at some point it will affect the cash flow, and thus shareholder value. 271 We therefore find it reasonable to deduct it from the cash flow during our forecast period, as ignoring it could lead to an overvaluation of LSG. For the purpose of this thesis, we have taken the very conservative approach of eliminating all deferred tax assets in the first forecast year, and thus estimate it to 0 for the entire forecast period. This leads to a cash outflow of 1 531 million NOK the first year of our forecast period. By doing this, we capture the effect deferred tax liabilities will have on shareholders value at some point in the future. The reason why we chose to use a very conservative approach, is that we find it a difficult task to calculate the timing of new investments that will impact deferred tax liabilities, and thus difficult to estimate future levels, and when they will be paid in full. 270 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 431. 271 Damodaran, Aswhat (2015) What should you subtract out to get to equity value? Stern School of Business, New York & New constructs (19.08.2013) Net deferred tax assets and liabilities Valuation adjustments 92

5.4.4 Net operating working capital Historically NWC has been varying a great deal, with a low of 26.2% (2011) and a high of 38.1% (2013), and the most important contributor has been biological assets. The forecasts above results in a rising NWC from 2015 to 2020, this is a result of more capital being tied up in biological assets, which is caused by the added maximum biomass allowed in the future. In 2015 and 2016, we estimate it to be stable at 31.7%, before it slowly starts to rise toward 33.2% of revenues in 2020, when maximum capacity utilization is reached. 5.4.5 Summary balance sheet forecast Our above estimates lead to the following pro forma balance sheet Table 5.10: pro forma balance sheet Forecasted balance sheet (1000 NOK) 2015E 2016E 2017E 2018E 2019E 2020E 2021E Non-current assets Deferred tax assets 26 543 28 259 30 407 30 049 29 606 30 448 31 210 Licenses and rights 2 161 685 2 185 572 2 303 116 2 383 576 2 538 001 2 698 208 2 765 663 Buildings, real estate, operating accessories 2 787 057 2 896 583 3 116 694 3 080 027 3 034 637 3 120 955 3 198 979 Shares in associates 504 325 536 927 577 729 570 932 562 518 578 519 592 982 Non-current receivables 21 235 22 607 24 325 24 039 23 685 24 359 24 968 Total non-current assets exl goodwill 5 500 845 5 669 949 6 052 270 6 088 623 6 188 448 6 452 489 6 613 801 Goodwill 2 082 706 2 082 706 2 082 706 2 082 706 2 082 706 2 082 706 2 134 774 Total non-current assets incl goodwill 7 583 551 7 752 655 8 134 976 8 171 329 8 271 154 8 535 195 8 748 575 Current assets Biological assets 3 915 152 4 168 253 4 561 015 4 567 454 4 544 554 4 719 494 4 837 481 Other inventories 464 510 494 538 532 118 525 858 518 109 532 846 546 167 Trade receivables 1 526 246 1 624 912 1 748 389 1 727 820 1 702 357 1 750 780 1 794 549 Other receivables 305 249 324 982 349 678 345 564 340 471 350 156 358 910 Total current assets 6 211 156 6 612 686 7 191 201 7 166 696 7 105 491 7 353 275 7 537 107 Non-interest bearing debt Trade payables 1 114 823 1 186 892 1 277 084 1 262 060 1 243 461 1 278 831 1 310 801 Public duties payables 99 538 105 973 114 025 112 684 111 023 114 181 117 036 Taxes payable 384 879 409 760 440 898 435 711 429 290 441 501 452 539 Other current liabilities 411 423 438 020 471 305 465 760 458 896 471 949 483 748 Total non-interest bearing debt excl deferred tax 2 010 663 2 140 645 2 303 313 2 276 215 2 242 671 2 306 462 2 364 124 Deferred tax liabilities - - - - - - - Total non-interest bearing debt incl deferred tax 2 010 663 2 140 645 2 303 313 2 276 215 2 242 671 2 306 462 2 364 124 Net working capital 4 200 493 4 472 041 4 887 888 4 890 481 4 862 821 5 046 813 5 172 984 Invested capital exlc goodwill and deferred tax 9 701 338 10 141 989 10 940 158 10 979 104 11 051 268 11 499 302 11 786 785 Invested capital inlc goodwill and deferred tax 11 784 044 12 224 695 13 022 864 13 061 810 13 133 974 13 582 008 13 921 559 Total equity 9 427 235 9 779 756 10 418 291 10 449 448 10 507 179 10 865 607 11 137 247 Net interest-bearing debt 2 356 809 2 444 939 2 604 573 2 612 362 2 626 795 2 716 402 2 784 312 Invested capital (financing) 11 784 044 12 224 695 13 022 864 13 061 810 13 133 974 13 582 008 13 921 559 Source: Authors creation 93

5.5 Forecast summary Graph 5.1: Historical and forecasted development of key ratios Source: Authors creation, Annual reports 2005-2014 To evaluate our pro forma statements, and to check the quality of our estimates, we have summarized Revenues, Invested capital, pre-tax ROIC, CAPEX, and average ROIC in the graph above. A key driver and focal point of analysis is LSG s measure of overall profitability, ROIC. 272 Our estimated pre-tax ROIC is stable and in line with the historical average, we find this development realistic as salmon prices are estimated to be high, maximum biomass is expected to grow, and efficiency through new technology is expected to be higher and costs are expected to be low. These factors will lead to a future high profit margin, and thus a high ROIC. Furthermore, our estimated pre-tax ROIC will peak at 17.4% in 2017, which is well below the peak of 26.2% in 2010, and the recent ROICs of 20.3% and 19% in 2013 and 2014 respectively. Our estimated average invested capital is also below revenue, and yields a steady turnover rate, with an average of 1.2, throughout the forecast period this is in line with historical figures, and the trend that LSG have a high turnover rate compared to the rest of the industry. We therefore conclude that our forecasts seem realistic and yield realistic key ratios for LSG in the forecast period. 272 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 195. 94

6 Cost of capital In order to get the best possible estimate of LSG s value, it is essential that we estimate the cost of capital as precisely as possible. This is to ensure that the future cash flows are discounted at the correct rate. As we will use free cash flows to firm in our valuation models, it is appropriate to use weighted average cost of capital (WACC) as our discount factor in our DCF and EVA valuation. WACC is defined as: 273, where E is the market value of equity, NIBD is the market value of net interest bearing debt, is the required rate of return on equity, is the required rate of return on debt, and is the corporate tax rate. In this part we will estimate the future capital structure, required rate of return and required rate on debt. 6.1 Capital structure LSG has a goal of keeping an equity ratio of at least 30% based in book values. 274 However, looking at the historic capital structure we find that this number has been substantially higher. Over the past 5 years the average equity ratio, based on market values, in the industry has been 71%. 275 For LSG the ratio has been 81% over the same period. The historic capital structure for LSG and the industry is summarized below, the complete version can be found in appendix 6.1. Table 6.1: Equity ratios based in market value equity and NIBD, LSG and peers Equity ratios Average last 5 years 17.04.2015 LSG 81 % 86 % SAL 71 % 84 % MHG 76 % 77 % GSF 55 % 65 % Industry average 71 % 78 % Source: compiled by authors, ARs 2008-2014, yahoo finance LSG s equity ratio has relatively stable over the 5 year period, with a low of 73% (2011) and a high of 88% (2014), and at the time of our cutoff date it was 86%. As we have calculated the ratio using market values of equity they are affected by the markets outlook for the company and industry the recent historically 273 Koller et al (2010) Valuation pg. 236 274 Lerøy Seafood - Annual Report (2014) pg. 24 275 Calculated as, 95

high value per share thus affect the ratio positively, and is the reason why the highest value was observed in 2014. 276 Using book values, we find the equity ratio to be 80% per 31.12.2014, which is consistent with our market value calculations. Furthermore, LSG have a goal of sustaining a high degree of financial flexibility in order to cope with the cyclical nature of the industry, as well as acquiring funding when profitable investment opportunities emerges. 277 We therefore estimate that LSG will fluctuate around their current capital structure, and estimate it to be 80% equity and 20% NIBD in all future periods. 6.2 Cost of equity ( ) The most used model to estimate the cost of equity is the capital asset price model (CAPM). Despite heavy criticism for being too unrealistic to use for a real world investor, it remains the go-to model for assessing risk and return, 278 and will thus be used to calculate LSG s cost of equity. The standard CAPM model is outlined below:, where is the required return on the company, is the return on a risk-free asset, = Beta of the company, and is the market risk premium (MRP) In the coming pages we will look at several sources of risk, and estimate the risk free rate, beta of LSG and the peer group, and the market risk premium. We will then put it all together to obtain the required rate of return on equity for LSG. Risk-free rate When estimating the risk-free rate the most used approach is to look at government default-free bonds. 279 In addition, you should always use government bonds issued in the same currency as the company s cash flows. Ideally we would like to match the maturity of each cash-flow with a default-free bond with the same maturity. 280 In practice this becomes an extremely hard, if not impossible task. The common practice is therefore to use a 10-year default-free bond as a proxy for the risk-free rate. We have chosen Norwegian risk free bonds as our proxy for the risk free rate. Bonds issued by the Norwegian central bank had a yield of 1.42% as of the 17 th of April 2015. 281 This is among the lowest in the history, and below the inflation goal of 2.5% set by the central bank, 282 and thus 276 See section 2.2.1 Historical events and share price development, page 18 277 Lerøy Seafood - Annual Report (2014) pg. 11 & 24 278 Koller et al (2010) Valuation pg. 36 279 Koller et al (2010) Valuation pg. 240 280 Koller et al (2010) Valuation pg. 240 281 www.norges-bank.no/en/statistics/interest-rates/government-bonds-daily/ 96

not sustainable in the long run as investors would require a return that is at least marginally higher than the inflation. We have thus collected information about the historic 10-year default-free bond yield, and computed average numbers for the last 5, 10 and 15 years respectively, the calculations can be found in appendix 6.2. After an overall assessment, we have decided to set the risk-free rate to 3.49% - the average over the last 10 years, and a 1% premium over the stated long term inflation goal. Beta ( ) In the CAPM, the beta is a measure of a company s systematic risk, which aims to measure the sensitivity of a company s returns to movements in a market portfolio usually the stock index where the company is listed. LSG s beta can be estimated in different ways, and we will look at some of them below. Regression on the market portfolio (OSEBX) In the traditional CAPM, beta is estimated by running a regression where LSG s historic returns are regressed on the market portfolios returns over a period of 5 years (60 monthly observations). As a proxy for the market portfolio we have used the OSEBX-index (hovedindeksen) on Oslo Børs - an index of carefully selected stocks listed on Oslo Børs, as of 17 th of April it counted 59 different companies. 283 Below you can find a summary of the raw betas for LSG and its peers from our regression on OSEBX, all regression outputs can be found in appendix 6.3. Table 6.2: Raw betas Raw betas LSG 0,84 GSF 0,81 MHG 0,78 SAL 0,95 Source: Authors' creation, yahoo finance The raw beta of LSG is estimated to 0.84 when using the OSEBX-index as the market portfolio, and a 5-year time period. We have also calculated the beta using 60 weekly observations, the results from this regression can be found in appendix 6.3, and yielded a beta value of 0.56. This shows that LSG s beta is not stable over time, and that there might be measurement problems in our estimations. 284 Furthermore, using historical data to estimate the future systematic risk assumes that the risk of the company remains stable over time. Our different beta estimations show that this is not the case for LSG, and might be a result of 282 www.norges-bank.no/en/statistics/inflation/ 283 www.oslobors.no/markedsaktivitet/#/details/osebx.ose/overview 284 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 253 97

changes in strategy and merger and acquisition activity. 285 To deal with potential measurement problems we will adjust our results using different approaches below. Adjustment of raw results Table 6.3: Relevered betas OSEBX raw β D/E* tax Unlevered βtarget D/E relevered β LSG 0,84 0,23 28 % 0,72 0,25 0,85 GSF 0,81 0,82 28 % 0,51 0,67 0,76 MHG 0,78 0,32 28 % 0,64 0,33 0,79 SAL 0,95 0,41 28 % 0,74 0,37 0,93 Industry average 0,85 0,44 28 % 0,65 0,40 0,83 Source: Compiled by authors' * Calculated using last 5 year average One way of adjusting a company s beta is to take the raw beta, adjust it for the capital structure over the 5- year period, and then adjust it back using the estimated future capital structure to find the estimated future beta value. This yields an estimated, re-levered beta of 0.85 for LSG. This seems a bit low, so we have followed Bloomberg s practice of adjusting the beta value to account for the fact that the beta tends to move toward the market average of 1 in the long run. 286 This yields an estimated beta value of 0.90 for LSG. Another approach of estimating the beta is to use the industry average unlevered beta as the basis, and then adjust for the capital structure to find the estimated future beta. For LSG this yields a beta value of 0.77, adjusted using Bloomberg s formula this becomes 0.84. Below we have summarized our estimations for LSG and the industry: Table 6.4: Adjusted betas, company and industry as basis Adjusted betas company as basis industry as basis LSG 0,90 0,84 GSF 0,84 0,97 MHG 0,86 0,87 SAL 0,95 0,88 Average 0,89 0,89 Source: compiled by authors' 285 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 253 286 Adjusted beta = 98

Beta values collected from online financial resources For comparison, we have also collected beta values for LSG and peers from several online financial sources, these are listed in table 6.5. Table 6.5: Collected betas Betas Reuters FT E24 (1 yr) CNBC Average LSG 0,99 0,99 0,54 0,99 0,88 GSF 0,86 0,86 0,77 0,86 0,84 MHG 0,75 0,75 0,72 1,02 0,81 SAL 1,04 1,04 0,54 1,04 0,92 Industry average 0,91 0,91 0,64 0,98 0,86 Source: Compiled by authors', Reuters, FT, E24, CNBC We can see that the American sources have the same beta for LSG, while the Norwegian source have a different result, which is likely to be a result of different time horizons used in beta estimations. The results also differ from our estimates, most likely due to a different benchmark index. All in all, they show that our estimate might be too low. Furthermore, we collected a beta estimate from Damodaran, who calculated the beta for European food processors to be 0.93. 287 Beta estimation from fundamental factors To investigate LSG s beta further, we have estimated it using fundamental factors as stipulated in Petersen & Plenborg. An overall assessment of the fundamental factors in operating activities can be found in appendix 6.4. From our assessment we conclude that LSG exhibits low to moderate risks when it comes to operating risk. An overall assessment of financial risk can be found in appendix 6.4. From this assessment we conclude that LSG exhibit low financial risk. An overall assessment of fundamental factors therefore put LSG in the category neutral operating risk and low financial risk, which corresponds to an equity beta value of 0.6-0.85. 288 We feel that it is appropriate to put LSG in the top end of this spectrum, and assign them a beta value around 0.85 from the fundamental analysis. Conclusion beta From our above analyses and collection of beta values from different sources, we have found evidence to support a beta estimation in the range of 0.85 to 0.99. We have decided to use a beta estimate of 0.92 for the purpose of this thesis. This number is close to Damodaran s estimate, and the average of the findings in our analyses (excluding the number from E24). We have also done the same for LSG s peers, our findings are summarized in table 6.6: 287 Damodaran (05.1.2015) Cost of Capital by Industry Sector, Stern School of Business, New York 288 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 262 99

Table 6.6: Conclusion beta Adjusted betas Collected betas company as basis industry as basis Financial sources Damodaran Average LSG 0,90 0,84 0,99 0,93 0,92 GSF 0,84 0,97 0,86 0,93 0,90 MHG 0,86 0,87 0,85 0,93 0,88 SAL 0,95 0,88 1,04 0,93 0,95 Average 0,89 0,89 0,94 0,93 0,91 Source: compiled by authors', Reuters, FT, CNBC, Damodaran Market risk premium ( The market risk premium is the added return investors require for taking on risk higher than the riskfree rate. The risk premium is a critical component when calculating WACC through CAPM, and should be a forward looking measure when used in valuation. 289 However, a forward looking risk premium is not observable in the market, so we have to rely on estimates largely based on historical data. For many years the norm has been to use an estimate of 5% in mature and functional markets. However, recent studies show that this number is likely to be too low. KPMG Netherlands estimated the MRP to 6.25% in April 2015, 290 Aswath Damodaran estimated it to be between 5.75% and 6.20% in the Norwegian market, 291 Market-risk-premium.com estimated it to 6.58%, 292 while Isabel Fernandez estimated it to be 5.8%. 293 The average of these calculations is 6.12%, and it thus seems reasonable to estimate a MRP higher than the 5% normally used. In section 6.2 we estimated that the risk-free rate will bounce back from its historically low level, which in turn will affect the MRP. We therefore find it reasonable to estimate a MRP below the average estimates found and choose to use a MRP of 6% in our CAPM model. 6.2.1 Conclusion cost of capital We now have all the inputs we need to calculate the cost of capital using CAPM. We do not find it necessary to add other risk parameters, as the higher than usual MRP reflects some of the added risk that might be present for the industry/lsg. The cost of capital calculation can be found below: 289 Pratt, Shannon P. (2002). Cost of Capital: Estimation and Applications, Second Edition. John Wiley & Sons. pg. 118 290 KPMG (02.04.2015) Equity Market Risk Premium Research Summary 291 Damodaran (January 2015) Country Default Spreads and Risk Premiums Stern School of Business, New York 292 http://www.market-risk-premia.com/no.html 293 www.valuewalk.com/2015/07/market-risk-premium-used-in-88-countries-in2014-a-survey 100

Our cost of equity estimation is close to that one done by Damodaran for the food processing industry (8.6%). 6.3 Cost of debt The cost of debt is the last input factor we need to calculate the WACC for LSG and its peers. Ideally we would look at long maturity bonds issued by the company and determine the yield of these bonds. 294 Unfortunately, LSG does not issue bonds, but have their debt in banks with a floating interest rate. This means that the cost of debt is variable over time, and we have to do a best estimate in order to determine the future cost of debt. Previously we estimated the risk-free rate as 3.49% - this is a good place to start our analysis. The cost of debt should not be lower than this, and is likely to be some percentage points over this level. We have looked at the fundamental factors using Moody s and standard and poor s credit rating systems, and found that both yielded LSG a high credit rating. These can be found in appendix 6.5. A high credit rating is typically awarded with a spread of 0.4% to 1.2% (Damodaran 2015). Looking at LSG s historical borrowing cost and comparing it with the historical risk-free rate we find evidence that suggests that this is too low. The average spread over the past 5 years has been 2.10%, and we feel this better reflect the real spread for the company. Also, the average cost of debt over the past 5 years has been 5.16%. Our findings are summarized below, and the same has been done for peers and peers in appendix 6.6: Table 6.7: Historic spread, LSG Cost of debt LSG 2010 2011 2012 2013 2014 5 yr average Risk-free 4,00 % 3,52 % 3,12 % 2,10 % 2,58 % 3,06 % LSG 4,90 % 5,70 % 4,90 % 4,60 % 5,70 % 5,16 % Spread 0,90 % 2,18 % 1,78 % 2,50 % 3,12 % 2,10 % Source: Compiled by authors, LSG annual reports 2009-2014 Taking all of the above analyses into account, we estimate the cost of debt to 5.2% for LSG, implying a spread of 1.71%. This is lower than the historical spread and higher than the spread estimated by Damodaran. However, we find it reasonable as it is close to what the spread has been when the riskfree rate has been in the 3-4% region. Furthermore, the cyclical nature of the company, discussed in section 2.2.6., is likely to affect the spread and borrowing cost negatively. 294 Koller et al. (2010) Valuation pg. 261 101

6.4 Conclusion Weighted average cost of capital We now have all the inputs we need to calculate LSG s and its pees WACC. A summary of WACC calculations can be found in table 6.8. WACC E/(NIBD+E) Re Rd WACC LSG 0,80 9,01 % 5,20 % 7,96 % GSF 0,60 8,89 % 5,16 % 6,82 % MHG 0,75 8,77 % 10,49 % 8,47 % SAL 0,73 9,19 % 4,89 % 7,66 % Source: Compiled by authors' As seen from the table, LSG s cost of capital is estimated at 7.96%. This is the number we will use throughout our valuation. The estimated WACC is based on a number of estimates and assumptions, and can heavily influence our valuation of LSG. As comparison Pareto used an estimated WACC of 8% in their valuation of the seafood industry, 295 while Damodaran estimates the WACC to be 7.6% for European food processing companies. 296 Later we will look at what happens to our valuation if we change our assumption about the cost of capital. Table 6.8: WACC LSG and peers 7. Valuation In this part we will estimate the value of LSG based on the pro forma statements in section 5. Throughout this thesis we have done our best to be objective, and find best estimates for all input factors for our valuation. Nevertheless, some of our estimates rely on assumption that can alter the value of the company significantly. We will therefore perform a sensitivity and scenario analysis, to see how sensitive our valuation is to changes in our assumptions about key drivers. This will lead us to a valuation range, and set our valuation model in perspective. There are several models available for valuation purposes. 297 In this thesis we will focus on present value models and relative valuation. In our present value approach we will use a discounted cash flow (DCF) model and an economic value added (EVA) model. We use two different models in order to ensure that all 295 Pareto - Seafood Research Report (10.04.2015) pg. 39 296 Damodaran (05.01.2015) Cost of Capital by Industry Sector, Stern School of Business, New York 297 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 210 102

calculations are done correctly, and this will be the case if both models yield the same result. We have chosen these models because of their robustness, close link to economic theory and competitive strategy, and that they are the most accurate and flexible method for valuing companies. 298 It is also the most used models by practitioners and investment banks. In the relative approach, we will use multiples to obtain the value of LSG. 7.1 Present value models In order to calculate the enterprise value of LSG, we need to find the free cash flow to firm (FCFF). Cash flow 2015E 2016E 2017E 2018E 2019E 2020E 2021E NOPAT 1 318 867 1 451 841 1 584 059 1 587 058 1 584 986 1 630 070 1 670 822 Change in deferred tax liabilities-1 531 262 - - - - - - Depreciation 384 614 399 728 430 104 425 044 418 780 430 692 441 459 Change in NWC -135 319-271 548-415 847-2 594 27 661-183 993-126 170 CAPEX -415 567-568 832-812 425-461 396-518 605-694 734-654 839 FCFF -378 667 1 011 189 785 890 1 548 112 1 512 823 1 182 036 1 331 272 Changes in NIBD 349 895 88 130 159 634 7 789 14 433 89 607 67 910 Net financial expenses after tax -81 689-89 889-97 515-97 807-98 347-101 702-104 245 FCFE -110 461 1 009 431 848 009 1 458 094 1 428 908 1 169 941 1 294 937 Dividend 110 461-1 009 431-848 009-1 458 094-1 428 908-1 169 941-1 294 937 Cash surplus - - - - - - - Source: Authors' creation Table 7.1: Estimated free cash flow, LSG Above we have calculated the FCFF for LSG over the entire forecast period. As discussed in section 5.4.3 (pg. 93), our decision to eliminate all deferred tax liabilities in the first year has a big impact on the cash flow, rendering it negative for the first year of our forecast. All other years we have a positive FCFF. The change in NWC is negative for all years except 2018, which is consistent with our assumptions that LSG will have more capital wound up in biological assets, as the MAB will increase over time. 299 Similarly the CAPEX is negative throughout the period, as a function of new investments in licenses and rights and operating accessories required to operate these new licenses. The NOPAT is increasing from 2015 until 2018. In 2018 the reduced spot price has a negative development on the NOPAT, but after the salmon price stabilizes the NOPAT has a positive development, as a result of more cost efficiency discussed in section 5.2.1 (pg. 87) 298 Koller et al (2010) Valuation pg. 103 & 313. 299 See section 5.4.1 (pg. 90) and section 5.4.4 (pg. 92) 103

7.1.1 Discounted cash flow (DCF) model Table 7.2: DCF model, LSG DCF 2015E 2016E 2017E 2018E 2019E 2020E 2021E FCFF -378 667 1 011 189 785 890 1 548 112 1 512 823 1 182 036 1 331 272 WACC 7,96 % 7,96 % 7,96 % 7,96 % 7,96 % 7,96 % 7,96 % Discount rate 0,926 0,858 0,795 0,736 0,682 0,632 0,585 Present value, FCFF -350 757 867 626 624 614 1 139 731 1 031 663 746 673 Present value of FCFF, forecast horizon 4 059 550 Present value of FCFF, terminal period 15 410 926 Estimated enterprise value 31.12.2014 19 470 476 NIBD 31.12.2014 2 006 914 Minority share (book value) 31.12.2014 817 282 Estimated value of equity 31.12.2014 16 646 280 Estimated value of equity 17.04.2015 17 024 112 Shares (1000) 54 577,37 Estimated price per share 311,9 Estimated market to book 2,1 Terminal value as % of EV 79,2 % Share price 17.04.2015 235,00 Upside potential 33 % Source: Authors' creation The DCF model relies on the estimated free cash flow to firm (FCFF) for our forecast period, calculated in section 7.1. The FCFF is then discounted at the WACC to derive at an estimated enterprise value of 19 470 million NOK per 31.12.2015. To calculate the value of equity we have to subtract the market value of NIBD and minority shares. As discussed previously, we have estimated the market value of NIBD to be equal the book value. Ideally we would like to calculate the market value of minority shares by looking at the historic return levels to estimate how big their share is of the overall value of LSG. Looking at the history, we find that this number have varied from -1.1% (2011) to 8.1% (2013), making it extremely difficult to estimate. We have therefore set it equal to book value as per 31.12.2014. This leaves us with an estimated value of equity of 16 646 million NOK as per 31.12.12014. To get the value on our cutoff date, we need to adjust it forward with the following formula: E*(1+WACC)^(107/365). This gives us an estimated value of equity of 17 024 million or 311.9 NOK per share on the 17.04.2015. 104

7.1.2 Economic value added model Table 7.3: EVA model, LSG EVA 2015E 2016E 2017E 2018E 2019E 2020E 2021E NOPAT 1 318 867 1 451 841 1 584 059 1 587 058 1 584 986 1 630 070 1 670 822 Invested capital begining of period 10 086 510 11 784 044 12 224 695 13 022 864 13 061 810 13 133 974 13 582 008 WACC 7,96 % 7,96 % 7,96 % 7,96 % 7,96 % 7,96 % 7,96 % Cost of capital 802 563 937 633 972 695 1 036 203 1 039 302 1 045 044 1 080 693 EVA 516 304 514 208 611 364 550 855 545 684 585 026 590 129 Discount factor 0,926 0,858 0,795 0,736 0,682 0,632 0,585 Present value of EVA 478 250 441 203 485 904 405 543 372 127 369 552 Invested capital beginning of period 10 086 510 Value of EVA in forecast period 2 552 579 Value of EVA in terminal period 6 831 387 Estimated enterprise value 31.12.2014 19 470 476 NIBD 31.12.2014 2 006 914 Minority share (book value) 31.12.2014 817 282 Estimated value of equity 31.12.2014 16 646 280 Estimated value of equity 17.04.2015 17 024 112 Shares (1000) 54 577,37 Estimated price per share 311,9 Estimated market to book 2,1 Terminal value as % of EV 35,1 % Share price 17.04.2015 235,00 Upside potential 33 % Source: Authors' creation As we use the same assumptions for both models, the EVA model yields the same result as the DCF model. The difference is that it ignores cash flows, and focus on NOPAT, invested capital, and the cost of capital each year. As we can see, LSG creates value for its owners every year, and the model is less sensitive to the terminal value 35.1% in our EVA model compared to 79.2% in the DCF model. 7.2 Relative valuation multiples Before we conclude our thesis and present an investment recommendation, we will value LSG by performing a relative valuation using multiples. This will enable us to triangulate our result by stress testing our DCF result. For our multiple valuation analysis, we will use the peer group and calculate our own multiples using 2014 numbers. We have also calculated 2015 estimates based on market consensus, all calculations can be found in appendix 7.2. Furthermore, we use the harmonic mean when valuating LSG based on multiples, as research has shown that this generates more accurate value estimates than multiples based on mean, median, and a value-weighted mean. 300 300 Petersen & Plenborg (2012) - Financial Statement Analysis pg. 234 105

7.2.1 Choice of multiples There are several alternative multiples to choose from when performing a relative valuation. We have chosen a sizeable selection of multiples that we believe fits our industry combined with multiples that are commonly used among analysts. The sizeable selection will also level out extremes. We have chosen the following multiples based on their advantages and disadvantages: Table 7.4: choices of multiples Multiple EV/Sales EV/EBITDA EV/EBIT EV/KG P/B Advantages and disadvantages + Least exposed to accounting differences + Applicable even with negative or highly cyclical earnings - A crude measure, since sales is rarely a direct value driver + EBITDA is a well-known proxy for free cash flow + Unaffected by depreciation policy + Focuses on core operations - Ignores variation in depreciation and capital expenditure - Ignores possible value creation through tax management + Allows for better differences in capital intensiveness compared to EBITDA by incorporating maintenance capital expenditure - Susceptible to variations in depreciation policy - Ignores possible value creation through tax management + Frequently used among analysts in the salmon industry + Focus on the core operations + Easy to understand competitors relative performance based on harvest volume + Not affected by accounting policies - Assumes that all other parts of operations are equal + Useful where assets are core driver of earnings, such as the salmon industry which is capital-intensive - Book value can be impacted by differences in accounting policies - Book value stated at historical cost, not a reliable indicator for economic value Source: Authors creation, Koller et al valuation (2010) pg. 313-333, Petersen & Plenborg, p 241-244 106

7.2.2 Multiple valuation Table 7.5: multiple valuation Multiple valuation EV/sales EV/EBITDA EV/EBIT P/B EV/KG 2014 2015E 2014 2015E 2014 2015E 2014 2015E 2014 2015E MHG 2,0 1,8 9,4 9,4 11,5 12,1 2,6 2,4 120,2 112,2 GSF 1,7 1,3 9,5 7,0 13,4 10,2 1,4 1,1 71,4 64,2 SALM 2,2 2,4 7,0 7,9 7,9 9,2 2,6 2,4 111,1 112,7 Harmonic mean 1,9 1,7 8,5 8,0 10,4 10,4 2,0 1,7 95,8 89,9 Estimated share price 388,6 362,8 297,4 280,8 308,4 307,1 295,7 299,7 226,0 221,8 Share price 17.08.2015 235 235 235 235 235 235 235 235 235 235 Upside potential 65 % 54 % 27 % 20 % 31 % 31 % 26 % 28 % -4 % -6 % High 444 532 342 338 412 366 392 409 297 291 Low 335 257 235 241 222 267 200 195 155 143 Source: Authors' creation, bloomberg As seen from the table above, all but one multiple show that there is upside potential in LSG and estimate a share price above the current level. EV/KG yields a negative upside potential. This is expected as LSG focus more on VAP and buying activities than the rest of the peer group, and thus create more of their value through other channels than the rest of the peer group, as discussed in section 3.2.2 and 4.1 (pg. 51-53). The highest valuation is from the EV/sales multiple, which is consistent with LSG generating more revenue from their activities. The EV/EBITDA and EV/EBIT multiples are thought of as the best multiples for comparing valuations across companies. This is because it is unbiased regarding capital structure and measures operating performance. 301 All of these show a significant potential upside in the share price. 7.4 Sensitivity analysis The estimates used in the valuation of LSG s share price is based on information from the strategic- and financial analysis, and influenced by our subjective opinion which might be biased. The valuation is therefore associated with uncertainty, which is why we perform a sensitivity analysis on our results from the DCF valuation. This way we check for simultaneous and individual robustness of the value drivers in our valuation model which again will reveal specific uncertainty related to different value drivers and their importance. Our factors in the sensitivity analysis are beta, risk-free rate, WACC, harvest volume, terminal growth rate and EBITDA margin. We have chosen to combine effects of changes in sales price and cost of materials into EBITDA/kg, as one unit decrease in cost of materials will give the same result as one unit increase in sales price. 301 Koller et al. (2010) Valuation pg. 314 107

Beta vs risk-free rate Beta Optimistic Realistic Pessimistic Risk-free rate 2,50 % 2,83 % 3,16 % 3,49 % 3,82 % 4,15 % 4,48 % Pessimistic 1,15 291 275 260 246 234 222 212 1,07 317 299 282 267 252 240 228 1,00 343 322 303 286 271 256 243 Realistic 0,92 378 353 332 312 294 278 263 0,85 413 385 360 337 317 299 282 0,77 461 427 397 371 347 326 307 Optimistic 0,70 511 471 436 405 378 353 332 Source: Authors' creation Even though we put a lot of attention and collected information from several trusted sources when calculating WACC in section 6, it is still an estimated value. An analysis of the input factors revealed that our calculated WACC is most sensitive to changes in risk-free rate and beta. In section 6.2 we found evidence to support a beta value in the range between 0.85 and 1. This makes up the realistic part of our analysis, and the share price here varies between 286 and 337. Our estimated risk-free rate was set at a level equal to the 10 year average return on 10-year bonds issued by the Norwegian government in section 6.2 (pg. 96). This value is higher than the observed 10-year bond rate in the last years, and might thus in reality be different from our estimate. In our realistic range the share price varies between 294 and 332 NOK, meaning that our valuation is sensitive to changes in risk-free rate, but not as much as to changes in beta. All in all, the realistic area yields a WACC between 7.4% and 8.6% and a share price between 271 and 360 NOK. This indicates that our valuation is sensitive to changes in input parameters in WACC. EBITDA/KG vs WACC EBITDA/kg Optimistic Realistic Pessimistic WACC 7,0 % 7,3 % 7,6 % 7,96 % 8,3 % 8,6 % 9,0 % Pessimistic -3 229 208 190 174 159 147 135-2 285 260 239 220 203 188 174-1 341 313 288 266 246 229 213 Realistic 0 398 365 337 312 290 270 252 1 454 417 386 358 333 311 291 2 510 470 435 404 376 352 330 Optimistic 3 566 522 484 450 420 393 369 Source: Authors' creation Figure 7.1: Beta vs risk-free rate Figure 7.2: EBITDA/kg vs WACC 108

Our previous analyses revealed that LSG s performance is highly sensitive to a change in EBITDA margin. It is thus important for us to check what happens to LSG s share price if our assumptions are wrong. The range of +/- 3 NOK per kilo in EBITDA/kg has been chosen based on the 5 year average historical development, where 2012 has been excluded. Isolated, these changes result in a share price between 174 and 450 NOK. However, we find these prices highly unrealistic based on historical development of EBITDA/kg, as a downswing is normally followed by an upswing which our sensitivity analysis fails to acknowledge. Furthermore, a significant and sustained drop in EBITDA/kg would likely trigger new innovation and cost cutting in the industry. A further restriction of numbers therefore seems appropriate. Constricting the change to +/- 1 NOK all years, as in the realistic part of the matrix, seems realistic and leads to a share price in the range of 266 to 358 NOK. Combining this with realistic changes in WACC yields a share price between 246 and 386 NOK. Growth rate vs WACC Figure 7.3: Terminal growth rate vs WACC Growth rate Optimistic Realistic Pessimistic WACC 7,0 % 7,3 % 7,6 % 7,96 % 8,3 % 8,6 % 9,0 % Pessimistic 1,75 % 344 319 297 277 259 243 228 2,00 % 360 333 309 288 268 251 236 2,25 % 378 348 322 299 279 260 244 Realistic 2,50 % 398 365 337 312 290 270 252 2,75 % 420 384 353 326 302 280 262 3,00 % 444 405 370 341 315 292 272 Optimistic 3,25 % 473 428 390 358 329 305 283 Source: Authors' creation In our DCF model, the terminal value accounts for 79.2% of the value of LSG. Our valuation is thus sensitive to changes in terminal growth. We believe that the growth rate is justified, but acknowledge that we might have misestimated it. As the estimated growth is low, we expect the upside to be larger than the downside. 109

Yield per license vs WACC Figure 7.4: Yield per license vs WACC Yield per license Optimistic Realistic Pessimistic WACC 7,0 % 7,3 % 7,6 % 8,0 % 8,3 % 8,6 % 9,0 % Pessimistic -15 % 339 312 288 267 249 232 217-10 % 359 330 304 282 262 245 229-5 % 378 347 320 297 276 257 240 Realistic 0 % 398 365 337 312 290 270 252 5 % 417 383 353 326 303 282 264 10 % 436 400 369 341 317 295 275 Optimistic 15 % 456 418 385 356 330 307 287 Source: Authors' creation In section 5.1.3 (pg. 85), we estimated that LSG will raise their yield per license as a result of better efficiency and new legislation. There is uncertainty related to our estimates, and the share price is thus sensitive to changes in yield per license. As LSG s historic numbers have been below the peer group average, we expect there to be more downside than upside in this parameter. All in all, we expect the uncertainty to come from the innermost squares from our sensitivity analyses above, and therefore estimate the share price interval to be within 246 and 386. 7.5 Scenario analysis In this section we will look at what happens if LSG s management decides to change their strategy, as well as look at what happens if several key factors changes at the same time. Our calculations will here be based on hypothetical situation, and as such we are forced to make best guess estimations in our model. 7.5.1 Scenario 1 strengthen focus on product innovation and VAP One of the opportunities recognized in the SWOT analysis is new markets for VAP and differentiated products. In particular the Chinese consumption of raw salmon is expected to triple over the coming years. Furthermore, the marked for raw products like sushi and shashimi has exploded in European countries over the last years. To examine how this possibly could influence LSG s value, we examine possible scenarios if they went all-in on value added products, and let costs run wild in order to gain a big market share in these high-end, high EBIT margin markets. 110

Best-case New products are well received in the market, and LSG takes a strong position in the growing raw salmon market in China, and continues to develop the market in Norway and the rest of Europe, resulting in a growing VAP focus and higher premiums at higher production costs. Sucessfull launch and product innovations 2015E 2016E 2017E 2018E 2019E 2020E 2021E Harvest volumes 166 000 177 620 188 277 197 691 205 599 213 823 219 168 Premium 1,95 2,00 2,20 2,40 2,60 2,80 2,80 Operating revenue 13 271 700 15 275 320 17 603 918 18 029 425 19 244 039 21 313 842 21 846 688 COGS per KG -51,2-52,0-56,0-58,0-60,0-62,0-62,0 Total operating costs per KG -66,9-68,9-74,4-76,0-78,4-81,6-81,6 EBIT/KG 11,4 15,3 17,2 13,4 13,3 16,0 16,0 NOPAT 1 357 090 1 958 332 2 329 373 1 904 925 1 963 137 2 466 398 2 528 058 FCFF -340 444 872 566 812 575 1 510 617 1 056 099 1 051 906 2 100 497 Estimated enterprise value 27 872 477 Estimated price per share 469 Upside compared to base case 50 % Source: authors' creation As seen from the table above, successfully raising their premium will yield a very high estimated price per share, even though they incur increasing costs. These input factors are highly uncertain, and our estimated cost level for such an increase in premium might be underestimated. Nevertheless, this is the absolute best case scenario for a strategy that involves going after the high EBIT margin segment, and our calculated EBIT of 16, is not that much above the one actually achieved at Lerøy Aurora which is where they produce most of their sushi and high EBIT products. Table 7.6: Scenario 1, best case Worst case Here, the new products fail as a result of import taxes and bans in Asia, and a diminishing demand for VAP products in Europe. As a result LSG does not get a higher sales premium, and they thus abandon the strategy after 2017 to reduce costs again, and go back to a normal production strategy, but still have to bear some of the costs associated with new launches. Table 7.7: Scenario 1, worst case Unsucessful launch and product innovation 2015E 2016E 2017E 2018E 2019E 2020E 2021E Harvest volumes 166 000 177 620 188 277 197 691 205 599 213 823 219 168 Premium 1,95 2,00 2,00 1,95 1,95 2,00 2,00 Operating revenue 13 271 700 15 275 320 16 003 562 14 648 908 14 433 029 15 224 173 15 604 777 COGS per KG -51,2-52,0-54,0-52,0-50,0-48,0-48,0 Total operating costs per KG -66,9-68,9-72,7-66,6-63,8-63,0-63,0 EBIT/KG 11,4 15,3 12,5 6,0 4,9 7,7 7,7 NOPAT 1 357 090 1 958 332 1 698 609 853 856 732 197 1 189 890 1 219 637 FCFF -340 444 872 566 1 090 974 1 484 379 657 977 529 024 880 087 Estimated enterprise value 13 355 932 Estimated price per share 197 Upside compared to base case -37 % Source: Authors' creation 111

As seen from the table above, a failed strategy leads to a stabile premium while the costs are increasing. This leads to a low EBIT, and the company thus abandon this strategy in order to cut costs, and survive. This results in a valuation of 197 per share. Again the input parameters are highly uncertain, but we feel they are realistic as such a failed strategy would put pressure on the company to change and seek higher margins through cost efficiency and targeting other markets. 7.5.2 Scenario 2 100% focus on cost efficiency Another strategy LSG can start implementing, is that of less VAP and buying and selling activities and focus solely on cost-efficient production. Best-case In this scenario, we would expect LSG to gradually reduce their costs toward the most cost-efficient producer SALM. If successful, they would reduce costs significantly, but they would also have to reduce their premium toward the industry average. This scenario is summarized below: Sucessfull cost-reduction w lower premium 2015E 2016E 2017E 2018E 2019E 2020E 2021E Harvest volumes 166 000 177 620 188 277 197 691 205 599 213 823 219 168 Premium 1,95 1,70 1,60 1,50 1,45 1,45 1,45 Operating revenue 13 271 700 12 984 022 12 802 850 11 268 390 10 732 252 11 037 525 11 313 463 COGS per KG -48,0-43,0-39,0-34,0-29,0-25,0-25,0 Total operating costs per KG -63,8-57,4-52,5-47,5-42,5-38,5-38,5 EBIT/KG 16,8 16,3 16,0 10,0 10,1 13,5 13,5 NOPAT 1 735 729 1 818 046 1 914 139 1 187 589 1 279 116 1 858 609 1 905 075 FCFF 38 195 2 022 509 1 834 599 1 933 782 1 399 219 1 489 727 1 626 032 Estimated enterprise value 23 733 722 Estimated price per share 422 Upside copmared to base case 35 % Source: Authors' creation As seen from the table a successful strategy would increase the value of the company. There is however a lot of uncertainty related to the cost per KG and premium in all estimated years, and we stress that this is a very optimistic scenario. Table 7.8: Scenario 2, best case 112

Worst-case If this strategy would fail for the group, we still expect costs to be reduced over the period, but at a slower rate. As a result, premium would also fall over the period, but would stabilize at a slightly higher level. This scenario is summarized below: A slower reduction in costs toward the historical average of the industry combined with a premium reduction toward industry average corresponds to a share price of 211. Again we reiterate that there is uncertainty regarding input parameters, but we still think it is a realistic scenario, should the group decide to follow a cost-leader strategy. Table 7.9: Scenario 2, worst-case Unsucessfull cost-reduction w lower premium 2015E 2016E 2017E 2018E 2019E 2020E 2021E Harvest volumes 166 000 177 620 188 277 197 691 205 599 213 823 219 168 Premium 1,95 1,70 1,60 1,50 1,50 1,50 1,50 Operating revenue 13 271 700 12 984 022 12 802 850 11 268 390 11 102 330 11 418 130 11 703 583 COGS per KG -48,0-45,0-41,0-37,0-33,0-32,0-32,0 Total operating costs per KG -63,8-59,4-54,5-50,5-46,5-45,5-45,5 EBIT/KG 14,5 12,2 12,1 5,3 6,4 6,8 6,8 NOPAT 1 735 729 1 562 273 1 643 020 760 576 948 041 1 049 418 1 075 654 FCFF 38 195 1 766 737 1 563 480 1 506 769 855 312 673 341 791 110 Estimated enterprise value 14 062 298 Estimated price per share 211 Upside copmared to base case -32 % Source: Authors' creation 7.5.3 Scenario 3 Changes in fundamental input factors In this section we will have a look at scenarios where key input factors changes simultaneously, and where LSG adjust their strategy accordingly without deviating too much from their present one. The sensitivity analysis revealed how sensitive LSG s stock price is to changes in our key drivers, and thus emphasizes the importance that our forecast assumptions are correct. Here we will look at how uncertainty related to sales price, harvest volume and cost of materials will affect the stock price. The analysis will look at the worst- and best-case within realistic expectations in the future, which is built on our SWOT summary. It can be found in table 7.10. 113

Table 7.10: Scenario 3 assumptions Source: Authors creation Our scenarios are quantified into cash flows and used as input in our valuation model, and can be found in appendix 7.3. The worst-case and best-case reveals two alternative prices with an interval between 182 and 486 NOK per share. The share price of 182 NOK from the worst-case represent a 42% downside compared to the base-case scenario. This price is close to the lowest price of LSG over the last year, where it was traded for 192. Our best-case scenario indicates a price of 486 NOK, which is an all-time high with an upside of 56% compared to our base-case scenario. As seen, changing multiple value drivers at the same time causes a significant impact in the estimated share price. With that being said, these two outcomes represent two extreme scenarios with regards to changes 114

in value drivers. Overall, we find the factors in the scenarios as realistic and relevant, but it is unlikely that all negative and positive effects will occur at the same time. It is also likely that LSG will adjust its strategy and operations with regards to different market conditions as they develop, either by reducing downside or by capitalizing on opportunities. 7.6 Summary valuation Figure 7.5: Valuation summary Source: Authors creation The estimated share price from all of our valuation methods are summarized in the table above. From our fundamental analysis and resulting DCF and EVA valuation, we estimated the share price to be 311.9 NOK, a potential upside of 33%. Our relative valuation indicated a fair value of LSG s share between 222 and 389, with an average of 299. Thus, our multiple analysis also showed a potential upside in the share. The average upside from all multiples used was 27%, whereas the most robust multiples 302 showed an upside of 20% (2014) and 31% (2015E). These results support our findings in the fundamental analysis, that LSG is current underpriced in the market. Our sensitivity analysis showed that LSG s share price is highly sensitive to changes in EBITDA/KG, and left us with a valuation range from 246 to 386 NOK per share. 302 EV/EBITDA and EV/EBIT 115

Furthermore, we calculated three possible scenarios. In two of the scenarios we estimated possible outcomes if LSG suddenly changed strategy. These gave us wide valuation ranges, and showed that there is more upside from a strategy where LSG follow a differentiated strategy, similar to the one they have to day. Finally, we hypothesized a scenario where several key input factors changes simultaneously, and saw that in extreme positive or negative situation, the share price can fluctuate between 182 and 486 NOK per share. 8. Discussion Although the share price is currently at historically high levels, we still estimate that there is a strong upside in LSG s share. Our fundamental analysis and consequent DCF and EVA-model revealed that there is a 33% upside in the share price. Among investment bank analysts, the consensus is that there is a big upside with an estimated share price of 303 per share. The investment banks range between 250 (Nordea Markets) and 342 (Pareto). This range in their valuations is large and suggests that market condition can change quickly in the industry, affecting the share price negatively or positively as shown in our sensitivity analysis. However, they all conclude that there is upside in the stock, which further validate our result. 116

9. Conclusion The purpose of our thesis was to find the fundamental value of LSG s equity, and the value of one stock of LSG. The financial and strategic analysis was the foundation of our forecasts and cash flow based valuation models. In addition we calculated LSG s share price by using multiples in our relative valuation, and performed sensitivity analyses and scenario analyses to validate and triangulate our DCF and EVA result. Our industry analysis revealed that salmon-farming is a cyclical industry, that the production cycle is long, and that Norway is one of the few countries in the world where conditions are close to ideal for salmon farming activities. The long production cycle makes it hard for supplier to adjust supply short term and leads to a high volatility in salmon prices, and thus performance. The key value drivers in the industry were identified as harvest volumes, salmon price, cost of materials, and VAP-premium through our financial and strategic analysis. Our financial analysis revealed that the industry has been highly profitable despite rising cost levels in recent years. This is because of historically high salmon prices in 2013 and 2014. This strengthened the suspicion that LSG s and the industry s performance is closely tied to the underlying salmon price. The financial analysis also showed that LSG is the revenue leader and cost loser in the industry. Even though they incur high costs compared to their peer group, they have still managed to deliver one of the highest ROIC and ROE in the industry. In our strategic analysis, we saw that LSG is able to deliver good results because of competitive advantages related to VAP-premium, and producing and selling high EBIT-margin products through their international network of distributors and strategic alliances around the world. Furthermore, their capacity utilization has been low, but is expected to increase as a result of technological advancements and better disease control. Limited amount of licenses, strict regulations, and high start-up costs were identified as advantages for the industry, but will also cap future growth for industry participants. Supply is thus expected to exhibit slow growth in the short term, which is positive for the development of the salmon price. New regulations are expected to be positive for harvest volumes in the medium and long term and are expected to have a negative effect on the salmon price in these periods. In the next section we estimated forecasts based on our previous analyses and conclusions, which led us to find an estimated share price of 311.9 for one LSG share through a DCF and EVA model. This result indicates that there is a substantial upside in the stock (33%). Our multiples valuations supported our findings in the cash flow models, and all but one showed a significant upside in LSG s share price. To stress test our results 117

we performed several sensitivity and scenario analyses, which showed that our estimated share price is highly sensitive to EBITDA/kg -and WACC estimates. They further revealed that LSG would be better off following a differentiated strategy, similar to the one they have now, then following a strategy where costefficiency is the main objective. The results above and throughout the thesis, leads us to conclude that there is a significant upside in LSG s share price, and we give a strong buy recommendation for potential investors. 118

10. Thesis in perspective This thesis is written at a time where the salmon industry and market outlook is going through a change. Historically there has been a lot of uncertainty and volatility in the market, especially regarding supply, and efficiency improvements have continuously changed the production phase. As a result, the supply is expected to be more predictable, which will have a stabilizing effect on the salmon price. On the other hand, demand is hard to predict, but is expected to be strong. How strong depends on a numbers of different factors prices on substitute products, possible trade restrictions, economic development etc. This makes it hard to predict the future salmon price, which is a significant value driver in our models. The industry operates in an environment where biological challenges are a big risk factor, and as such it is likely that disease outbreaks are likely to have strong effects in the market like the outbreak in Chile. These are hard, if not impossible, to predict, but it would be interesting to investigate how potential hazards affect the value of LSG. It would also be interesting to investigate how the new legislation allowing for onshore production of salmon would affect LSG. This area is however highly uncertain, and seeing how none of the big companies has started production on land it is hard to speculate in how this would affect the industry. Because of time and space limitations, we did not forecast explicit takeover targets. It would be interesting to see how such takeovers would affect the value of LSG going forward. We also calculated harvest volumes and VAP on an aggregated level. Here we could go deeper into each production facility/region to investigate individual value drivers for each region, and then value each region by its self before adding them all together to find the value of LSG. This would however require inside information and deep knowledge about each company in the group. In general we are positive about the market outlook for the entire industry, and as such it would be interesting to perform a valuation for more companies in the salmon-farming industry. 119

11. References Books Petersen, Christian V. & Plenborg, Thomas (2012). Financial Statement Analysis. Harlow: Pearson Viebig,J. Poddig,T. and Varmaz,A. (2008). Equity Valuation: Models from Leading Investment Banks. 5 th edition. John Wiley & Sons. Koller,T. Goedhart,M. and Wessels,D. (2010). Valuation: Measuring and Managing the Value of Companies. 5 th edition. John Wiley & Sons. Pratt, Shannon P. (2002). Cost of Capital: Estimation and Applications, Second Edition. John Wiley & Sons. Internet sources - Lerøy Seafood Group www.leroyseafood.com - Marine Harvest www.marineharvest.no - SalMar www.salmar.no - Grieg Seafood www.griegseafood.no - Cermaq Group www.cermaq.com - FishPool www.fishpool.eu - Oslo Stock Exchange www.oslobors.no - Bloomberg Online www.bloomberg.com - Norges Bank www.norges-bank.no - Norges Friskeri- og Kysthistorie www.norges-fiskeri-og-kysthistorie.b.uib.no - LovData www.lovdata.no - Knoema www.knoema.com - Population Institute www.populationinstitute.org - Fiskeri- og Havbruksnæringens forskingsforbund www.fhf.no - Veterinærinstituttet www.vetinst.no - Fiskeridirektoratet www.fiskeridir.no - Regjeringen www.regjeringen.no - Norges Sjømatråd www.seafood.no - Yahoo Finance www.finance.yahoo.com - Market-Risk-Premia www.market-risk-premia.com 120

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12. Appendix Part 1... 127 Appendix 1.1 - Table of tables... 127 Appendix 1.2 - Table of figures... 128 Appendix 1.3 Table of graphs... 128 Appendix 1.4 - Dictionary and abbreviations... 129 Part 2... 130 Appendix 2.1 Total Harvest quantity Atlantic salmon 1994-2014E... 130 Appendix 2.2 Salmon production cycle... 130 Appendix 2.3 Strategic events since 2000 Lerøy Seafood... 131 Financial analysis... 132 Appendix 3.1 Reformulated income statement and balance sheet for LSG and peers... 132 Appendix 3.2 DuPont structure with formulas... 140 Appendix 3.3 Index- and common size analysis... 141 Appendix 3.4 - Key financial- and liquidity ratios LSG and peers... 148 Appendix 3.5 Standard deviation revenues... 151 Strategic analysis... 152 Appendix 4.1 Porters five forces model... 152 Appendix 4.2 Export volumes 2014-2015 from Norway... 153 Appendix 4.3 Yearly salmon consumption... 153 Forecast... 153 Appendix 5.1 - Regression model with supply and European Union GDP growth... 154 Appendix 5.2 Supply and Demand regression input... 158 Appendix 5.3 Forecast supply and demand... 158 Appendix 5.4 - Fish pool forward price and eight investments banks salmon price forecast... 159 Appendix 5.5 Correlation between spot price and sales premium... 159 Appendix 5.6 Growth harvest volumes... 159 Appendix 5.7 - Forecast Assumptions... 160 Appendix 5.8 Forecast Assumptions KG... 162 Appendix 5.9 Forecast Income Statement & balance sheet KG... 164 Appendix 5.10 Historical sales premium LSG and peers... 165 Cost of Capital... 166 Appendix 6.1- Historical capital structure LSG and peers... 166 Appendix 6.2 Default-free bond yield 1998 2014... 167 Appendix 6.3 - BETA calculations... 168 Appendix 6.4 Operating- and financial Risk... 171 Appendix 6.5 Credit Rating... 171 Appendix 6.6 Cost of debt... 172 Valuation... 173 Appendix 7.1 FCFF... 173 Appendix 7.2 Multiples... 173 Appendix 7.3 Scenario 3, Changes in fundamental input factors... 175 126

Part 1 Appendix 1.1 - Table of tables Table 2.1: Harvest Volume per region. 13 Table 2.2: Detailed cost level per region...17 Table 2.3: Correlation between stock prices and salmon price.. 18 Table 2.4: Ownership structure as of 31.12.2014...26 Table 2.5: Key figures LSG and peer group...29 Table 3.1: Historical operating cost, LSG..38 Table 3.2: FGEAR LSG.....42 Table 3.3: FGEAR peer group.42 Table 3.4: Spread LSG.43 Table 3.5: Short-term liquidity ratios, LSG and peer group..44 Table 3.6: Long-term liquidity ratios, LSG and peer group. 45 Table 3.7: Financial statement summary, strength and weaknesses. 47 Table 4.1: Yield per license, LSG..50 Table 4.2: Sales premium, LSG and industry...52 Table 4.3: Salmon vs other protein sources. 59 Table 4.4: Global supply 2012-2017E..71 Table 4.5: SWOT...77 Table 5.1: Supply and demand regression output..80 Table 5.2: Salmon price and estimated future price.. 80 Table 5.3: Forecasted salmon prices...82 Table 5.4: Expected vs actual harvest volume, LSG...84 Table 5.5: Forecasted harvest volumes.85 Table 5.6: Forecasted sales premium..86 Table 5.7: Forecasted operation revenues..86 Table 5.8: Pro forma income statement...89 Table 5.9: Forecasted licenses and rights.91 Table 5.10: Pro forma balance sheet 93 Table 6.1: Equity ratios based in market value equity and NIBD, LSG and peers......95 Table 6.2: Raw betas 97 Table 6.3: Relevered Betas. 98 Table 6.4: Adjusted betas, company and industry as basis....98 Table 6.5: Collected betas 99 Table 6.6: Conclusion beta...100 Table 6.7: Historic spread, LSG.. 101 Table 6.8: WACC LSG and competitors...102 Table 7.1: Estimated free cash flow, LSG...103 Table 7.2: DCF model, LSG 104 Table 7.3: EVA model, LSG 105 Table 7.4: Choices of multiples... 106 Table 7.5: Multiple valuation.... 107 Table 7.6: Scenario 1, best case... 111 Table 7.7: Scenario 1, worst case....111 Table 7.8: Scenario 2, best case...112 127

Table 7.9: Scenario 2, worst-case....113 Table 7.10: Scenario 3, assumptions....114 Appendix 1.2 - Table of figures Figure 1.1: Structure of thesis.... 9 Figure 2.1: Overview salmon markets and supply flow......13 Figure 2.2: LSG s value chain....20 Figure 2.3: LSG s Corporate structure....22 Figure 2.4: Harvest volume per region, LSG.....22 Figure 2.5: Geographical location farming.....22 Figure 2.6: Geographical location S&D.. 24 Figure 2.7: Peer group selection....28 Figure 4.1: Summary VRIO analysis.....54 Figure 4.2: Fish feed companies..57 Figure 4.3: Summary Porters five forces... 61 Figure 4.4: PESTEL analysis....62 Figure 7.1: Beta vs risk-free rate.....108 Figure 7.2: EBITDA/kg vs WACC...108 Figure 7.3: Terminal growth rate vs WACC.109 Figure 7.4: Yield per license vs WACC...110 Figure 7.5: Valuation summary......115 Appendix 1.3 Table of graphs Graph 2.1: License development from 1992-2014, Norway...15 Graph 2.2: Historic price, cost and EBIT per kg.....17 Graph 2.3: Share price development and important historical events....18 Graph 2.4: Historical performance LSG.... 27 Graph 2.5: ROIC vs Avg. salmon price..27 Graph 3.1: Historical ROIC vs WACC.... 36 Graph 3.2: Historical ROIC LSG and peer group......36 Graph 3.3: Operating revenue per kg, LSG and peer group.. 37 Graph 3.4: Operating cost per kg, LSG and peer group...39 Graph 3.5: EBIT margin, LSG and peer group.. 39 Graph 3.6: Turnover rate invested capital, LSG and peers.....40 Graph 3.7: Indexing invested capital, LSG and peers......41 Graph 3.8: ROE after tax, LSG and peer group 43 Graph 3.9: Profitability map, LSG and peer group.....47 Graph 4.1: Yield per license, LSG and peer group... 50 Graph 4.2: Relative price development, protein sources... 59 Graph 4.3: Projected key rate Norway.. 65 Graph 4.4: Sea temperature..68 Graph 4.5: Salmon price development 2006-2015..70 Graph 4.6: Change in price and supply...70 128

Graph 4.7: Standing biomass. 72 Graph 4.8: Smolt release.... 73 Graph 4.9: Fish feed........74 Graph 5.1: Historical and forecasted development of key ratios. 94 Appendix 1.4 - Dictionary and abbreviations Biomass: The total weight of live fish where the number of the fish is multiplied with an average weight. HOG: Head on gutted (quantity measure) MAB: Maximum allowed biomass. Tons biomass which the farmer is allowed to have in the sea per license at a specific time. Smolt: Eggs which is put into fresh water will grow to juvenile fish (smolt). When it has reached a size of 100g, then it is ready to grow in the seawater. Post-Smolt: Post-smolt is the name of the fish when it is growing from a smolt of 100gram in the freshwater towards its first growth phase in the seawater plants GWT: Gutted weighted tons (quantity measure) License: A permission from the government in order to operate with fish farming. 780 tons of MAB in all of Norway except Finnmark and Troms which has 945 tons. Life cycle: The life cycle of the salmon is between 24-36 months in Norway, depending on the seawater temperature. The salmon is slaughtered around 4-5 kg. Processing: Fillets, ready-to-eat meals, portioning etc. 129

Part 2 Appendix 2.1 Total Harvest quantity Atlantic salmon 1994-2014E Source: Marine Harvest Handbook (2014 page 17) Appendix 2.2 Salmon production cycle Source: Marine Harvest Handbook (2014 page 74) 130

Appendix 2.3 Strategic events since 2000 Lerøy Seafood Source: Own creation / Lerøy Seafood Group Annual Report (2014) Strategic events since 2000 2000 Infusion of capital 2001 Investment in Scottish Sea Farms Ltd 2001 Investment in distribution in Sweden 2002 Infusion of Capital 2002 Listing on Stock Exchange 2002 Investment in smoking company in Sweden 2003 Acquisition of Lerøy Midnor AS 2003 Infusion of capital 2004 Acquisition of 60% of shares in Portnor Lda 2005 Partnership with Alarko Holding in Turkey 2005 Infusion of capital 2005 Acquisition of Lerøy Aurora Group 2005 Acquisition of Laksefjord AS 2005 Investments in distribution in Norway and Sweden 2005 Bulandet Fiskeindustri AS included in group structure 2006 Investments resulting in nationwide distribution of fresh fish 2006 Acquisition of Lerøy Fossen AS 2006 Infusion of capital 2006 Purchase of 100% of the shares in Lerøy Hydro Tech AS 2007 Infusion of capital 2007 Purchase of 100% of the shares in Lerøy Vest AS 2008 Austevoll seafood group ASA increases ownership of LSG ASA from 33.34% to 74.93% through a mandatory offer 2009 Austevoll seafood group ASA reduces its ownership of LSG ASA from 74.93% to 63.73% 2010 Purchase of 50.71% of the shares in Sjøtroll Havbruk AS 2012 Purchase of 50.1% of the shares in the dutch processing company Rhode Beheer B.V. 2012 Strategic agreement with SalMar for harvesting and processing of fish at the Innovamar plant in Frøya and at LSG's plant at Skjervøy. Close down of Lerøy Hydrotech's slaughterhouse in Kriatiansund 2013 Acquisition of 49.4% of the shares in the fish farming company villa organic AS 2013 Official opening of the new reciruclation plant for smolt production in Belsvik, Sør-Trøndelag 2013 Extension to Lerøy Fossen's production facilities in Hordaland ans Lerøy Smøgen in Sweden 2013 Investments in new fish cut facilities in Norway (Sjømarhuset), France, Spain and Denmark 2014 Increased investment in cleaner fish, among these the purchase of 34% of the shares in Norsk Opdrettsservice AS 2014 8 Licences from Villa Organic AS were merged into Lerøy Aurora 131

Financial analysis Appendix 3.1 Reformulated income statement and balance sheet for LSG and peers Source: Annual Reports Lerøy Seafood, Marine Harvest, SalMar and Grieg Seafood (2006-2014) Lerøy Seafood Group Reformulated Income Statement Income statement (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenue Operating revenues 4 014 454 5 616 592 6 290 898 6 057 053 7 473 807 8 887 671 9 176 873 9 102 941 10 764 714 12 579 465 Other revenues - - - - - - - - 53 805 117 409 Total revenues 4 014 454 5 616 592 6 290 898 6 057 053 7 473 807 8 887 671 9 176 873 9 102 941 10 818 519 12 696 874 Income from associated companies 77 052 128 982 35 509 13 716 62 744 122 006 19 741 24 831 192 188 91 939 Total revenues including income from associates 4 091 506 5 745 574 6 326 407 6 070 769 7 536 551 9 009 677 9 196 614 9 127 772 11 010 707 12 788 813 Operating costs Cost of materials -3 254 686-4 105 186-4 698 675-4 455 703-5 177 492-5 479 869-6 184 793-6 499 768-7 039 813-8 450 392 Salaries and other personnel costs -245 819-399 999-579 004-664 377-690 477-777 845-967 789-1 031 872-1 094 464-1 270 880 Other operating costs -191 625-342 943-472 158-579 295-586 743-691 791-858 107-853 884-1 004 148-1 262 518 Change in inventories - - - 176 551 135 068-132 291 318 613 57 449 258 380 447 053 Total operating costs -3 692 130-4 848 128-5 749 837-5 522 824-6 319 644-7 081 796-7 692 076-8 328 075-8 880 045-10 536 737 EBITDA 399 376 897 446 576 570 547 945 1 216 907 1 927 881 1 504 538 799 697 2 130 662 2 252 076 Depreciation -48 214-84 707-153 846-197 023-204 007-219 624-271 899-291 768-307 175-369 480 EBIT 351 162 812 739 422 724 350 922 1 012 900 1 708 257 1 232 639 507 929 1 823 487 1 882 596 Tax on operation profit -78 776-194 987-102 306-79 136-263 810-449 795-360 148-137 616-436 674-432 018 Net operating profit after tax (NOPAT) 272 386 617 752 320 418 271 786 749 090 1 258 462 872 491 370 313 1 386 813 1 450 578 Non-Operating items 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net financial items -17 090-40 294-69 736-150 507-86 105-66 272-81 884-95 153-101 840-119 790 Tax shield net financial items 3 834 9 667 16 877 33 941 22 426 17 450 23 925 25 780 24 388 27 489 Net financial expenses after tax -13 256-30 627-52 859-116 566-63 679-48 822-57 959-69 373-77 452-92 301 Impairment loss - - - - - - - -33 000-5 500-1 982 Adjustment of biomass to fair value 78 290 85 938 15 838-36 369 60 483 298 538-615 767 294 735 764 229-327 414 Special items after tax 60 727 65 320 12 005-28 167 44 730 219 931-435 854 190 821 577 035-253 806 Net profit 319 857 652 445 279 564 127 052 730 141 1 429 570 378 677 491 761 1 886 395 1 104 471 tax 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Tax on EBT 92 505 205 938 89 262 36 994 257 137 510 952 156 311 182 749 593 981 328 939 EBT 412 362 858 383 368 826 164 046 987 278 1 940 521 534 988 674 509 2 480 376 1 433 411 Effective tax rate 22,43 % 23,99 % 24,20 % 22,55 % 26,05 % 26,33 % 29,22 % 27,09 % 23,95 % 22,95 % 132

Lerøy Seafood Group Reformulated Balance Sheet Balance (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Non-current assets Deferred tax assets - - - - 4 461 3 697 6 546 21 545 11 807 42 263 Licenses and rights 309 400 764 587 1 183 089 1 291 624 1 289 977 1 972 239 1 981 726 1 978 924 1 978 656 2 151 685 Buildings, real estate, operating accessories 284 832 695 062 1 149 128 1 294 818 1 225 399 1 586 334 1 836 384 2 094 539 2 377 012 2 676 716 Shares in associates 336 144 308 592 289 474 277 455 272 970 338 864 329 168 331 056 735 071 566 965 Non-current receivables 1 621 244 681 6 274 11 928 8 129 8 453 8 607 26 171 32 263 Total non-current assets, exl goodwill 931 997 1 768 485 2 622 372 2 870 171 2 804 735 3 909 263 4 162 277 4 434 671 5 128 717 5 469 892 Goodwill 134 508 1 157 761 1 649 216 1 668 303 1 669 634 1 875 521 1 897 147 1 993 129 2 008 485 2 082 706 Total non-current assets, incl goodwill 1 066 505 2 926 246 4 271 588 4 538 474 4 474 369 5 784 784 6 059 424 6 427 800 7 137 202 7 552 598 Current assets Biological assets 542 829 1 052 319 1 494 133 1 676 164 1 858 562 2 706 733 2 370 938 2 724 941 3 727 361 3 681 993 Other inventories 95 337 189 326 265 008 223 158 236 311 290 379 328 045 326 225 358 482 524 947 Trade receivables 594 752 752 676 690 800 772 440 876 127 1 013 932 934 443 995 289 1 486 428 1 427 796 Other receivables 83 065 169 539 219 885 159 844 130 734 176 282 148 395 199 083 316 192 302 692 Total current assets (operating) 1 315 983 2 163 860 2 669 826 2 831 606 3 101 734 4 187 326 3 781 821 4 245 538 5 888 463 5 937 428 Non-interest bearing debt Trade payables 373 030 468 529 508 294 544 757 615 996 638 213 705 165 826 677 1 059 434 1 053 524 Public duties payables 12 182 32 963 37 743 49 014 55 671 74 312 62 386 66 915 103 656 70 073 Taxes payable 19 206 153 513 76 154 16 631 93 551 395 233 322 105 88 925 320 344 335 062 Other current liabilities 118 914 190 310 158 242 206 081 240 228 323 976 285 410 230 400 305 074 413 595 Total non-interest bearing debt, excl deferred tax 523 332 845 315 780 433 816 483 1 005 446 1 431 734 1 375 066 1 212 917 1 788 508 1 872 254 Deferred tax liabilities 158 354 451 172 643 529 669 327 834 877 1 260 028 1 083 693 1 230 458 1 486 972 1 531 262 Total non-interest bearing debt, incl deferred tax 681 686 1 296 487 1 423 962 1 485 810 1 840 323 2 691 762 2 458 759 2 443 375 3 275 480 3 403 516 Net working capital 792 651 1 318 545 1 889 393 2 015 123 2 096 288 2 755 592 2 406 755 3 032 621 4 099 955 4 065 174 Invested capital, excl goodwill 1 566 294 2 635 858 3 868 236 4 215 967 4 066 146 5 404 827 5 485 339 6 236 834 7 741 700 8 003 804 Goodwill 134 508 1 157 761 1 649 216 1 668 303 1 669 634 1 875 521 1 897 147 1 993 129 2 008 485 2 082 706 Invested capital, incl goodwill 1 700 802 3 793 619 5 517 452 5 884 270 5 735 780 7 280 348 7 382 486 8 229 963 9 750 185 10 086 510 Equity and Debt (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total equity 1 301 811 2 340 719 3 778 843 3 764 343 4 300 256 5 994 274 5 797 766 5 963 956 7 548 947 8 079 596 Net interest bearing debt Long-term interest-bearing debt 458 545 1 577 997 1 724 699 1 672 761 1 504 707 2 221 701 2 429 365 2 402 770 2 356 803 2 767 118 Other long term debt - - - 4 150 826 1 312 - - - - Other non-current liabilities - - - - - - 7 168 44 782 36 700 131 980 Pension liabilities 4 191 8 869 12 012 13 211 14 990 9 025 7 812 7 646 3 227 6 878 Short-term loans 131 082 382 003 566 594 841 921 646 105 434 121 760 977 911 887 682 574 469 276 Interest bearing-debt 593 818 1 968 869 2 303 305 2 532 043 2 166 628 2 666 159 3 205 322 3 367 085 3 079 304 3 375 252 Securities Cash and cash equivalents 191 157 509 872 537 738 388 486 707 989 1 357 096 1 597 429 1 082 797 872 513 1 360 272 Shares available for sale 2 615 5 737 26 423 23 161 23 115 22 989 23 173 18 281 5 553 8 066 Pension funds 245 360 535 469 - - - - - - Shares and securities 810 - - - - - - - - - Interest-bearing assets 194 827 515 969 564 696 412 116 731 104 1 380 085 1 620 602 1 101 078 878 066 1 368 338 Net interest-bearing debt 398 991 1 452 900 1 738 609 2 119 927 1 435 524 1 286 074 1 584 720 2 266 007 2 201 238 2 006 914 Invested capital (financing) 1 700 802 3 793 619 5 517 452 5 884 270 5 735 780 7 280 348 7 382 486 8 229 963 9 750 185 10 086 510 133

Marine Harvest Reformulated Income Statement Adjustments made due to operating leases 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net operating lease 0 0 0 0 34 400 30 500 184 200 165 000 290 700 385 400 Interest 0 0 0 0 11 352 10 065 60 786 54 450 95 931 127 182 Depreciation 0 0 0 0 23 048 20 435 123 414 110 550 194 769 258 218 Multiplier 0 0 0 0 6 6 6 6 6 6 Assets and NIBD 0 0 0 0 206 400 183 000 1 105 200 990 000 1 744 200 2 312 400 Income statement (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenue Operating revenue 1 501 300 5 640 500 14 091 500 13 486 900 14 619 500 15 281 200 16 132 800 15 420 400 19 177 300 25 300 400 Other revenues - - - - - - - 43 200 22 100 230 900 Total Revenue 1 501 300 5 640 500 14 091 500 13 486 900 14 619 500 15 281 200 16 132 800 15 463 600 19 199 400 25 531 300 Income from associated companies 1 400 23 700 66 600 5 800 69 500 202 000-8 500 88 300 221 800 149 500 Total revenues including income from associates 1 502 700 5 664 200 14 158 100 13 492 700 14 689 000 15 483 200 16 124 300 15 551 900 19 421 200 25 680 800 Operating costs Cost of materials -898 700-3 296 700-9 104 200-8 733 900-8 796 600-7 780 700-8 398 600-9 666 500-9 998 500-13 677 400 Salary and personnel expenses -255 100-839 500-2 165 000-2 139 800-2 167 400-2 202 500-2 177 800-2 418 700-2 674 300-3 320 900 Other operating expenses, adj -197 700-871 100-1 304 300-1 393 800-1 413 800-1 423 300-1 879 000-1 998 500-2 291 200-2 964 600 Change in inventory and biological assets, at cost 124 700 511 900-41 900 79 500 - - - - - - Total operating costs -1 226 800-4 495 400-12 615 400-12 188 000-12 377 800-11 406 500-12 455 400-14 083 700-14 964 000-19 962 900 EBITDA, adj 275 900 1 168 800 1 542 700 1 304 700 2 311 200 4 076 700 3 668 900 1 468 200 4 457 200 5 717 900 Depreciation and amortization, adj -139 100-305 500-791 800-685 300-710 748-673 435-790 114-787 750-957 269-1 225 018 EBIT, adj 136 800 863 300 750 900 619 400 1 600 452 3 403 265 2 878 786 680 450 3 499 931 4 492 882 Tax on operational profit -3 538 623 159-562 411-77 736-345 343-915 503-545 176-324 578-1 039 431-2 272 582 Net operating profit after tax (NOPAT) 133 262 1 486 459 188 489 541 664 1 255 109 2 487 762 2 333 610 355 872 2 460 500 2 220 300 Non-Operating items 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net financial items -73 700 152 600-44 700-1 781 500 312 800-208 900 172 500-179 500-1 204 300-2 146 700 Interest expense, capitalized leases - - - - -11 352-10 065-60 786-54 450-95 931-127 182 Tax shield financial assets 1 906 110 152 33 480 223 582-65 046 58 903-21 156 111 595 386 151 1 150 171 Net financial expenses after tax -71 794 262 752-11 220-1 557 918 236 402-160 062 90 558-122 355-914 080-1 123 711 Impairment losses/write downs/reversal 252 000 - -12 100-1 579 400-373 100-5 000-67 000-500 -65 000-24 100 Fair value uplift on harvested fish - - -750 000-80 400 - - - -1 575 800-4 323 700-5 518 500 Fair value adjustment on biological assets 71 600 40 000 399 600-198 400 301 200 1 091 700-1 514 000 1 926 000 6 118 300 5 007 700 Provisions for onerous contracts - - - - - -14 300-5 800-6 100-124 700 23 700 Restructuring costs - -41 400-196 300-241 000-169 500-4 400-21 800-800 -272 800-52 900 other non-operational items - - - - - - - - -74 400-168 200 Total special items 323 600-1 400-558 800-2 099 200-241 400 1 068 000-1 608 600 342 800 1 257 700-732 300 Special items after tax 315 232-2 411-140 269-1 835 746-189 311 780 700-1 303 968 179 283 884 180-361 889 Net profit continuing operations 376 700 1 746 800 37 000-2 852 000 1 302 200 3 108 400 1 120 200 412 800 2 430 600 734 700 Tax 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Tax on EBT 10 000-732 300 110 400-409 300 358 300 1 143 900 261 700 376 500 1 026 800 752 000 EBT 386 700 1 014 500 147 400-3 261 300 1 660 500 4 252 300 1 381 900 789 300 3 457 400 1 486 700 Effective tax rate 2,59 % -72,18 % 74,90 % 12,55 % 21,58 % 26,90 % 18,94 % 47,70 % 29,70 % 50,58 % 134

Marine Harvest Reformulated Balance Sheet Balance (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Non-current assets Deferred tax assets - 617 500 27 000 230 500 54 500 118 600 160 100 73 900 178 800 147 300 Licenses and rights 1 037 800 5 913 400 5 566 600 5 766 600 5 409 500 5 442 500 5 577 500 5 435 400 6 036 100 6 514 900 Propertry, plant and equipment 1 205 800 4 211 800 3 894 700 4 243 600 3 518 100 3 885 100 4 167 500 4 111 900 6 677 200 8 257 200 Investments in assoiciated companies 54 186 507 400 541 100 513 500 520 100 678 900 624 400 647 300 900 400 978 200 Other intangible assets 10 300 224 000 135 900 160 000 136 000 132 900 123 100 114 100 188 500 166 500 Fixed assets, capitalized leases - - - - 206 400 183 000 1 105 200 990 000 1 744 200 2 312 400 Other non-current assets 14 812 - - - - 2 600 25 800 73 200 8 900 14 500 Total non-current assets, excl goodwill 2 322 898 11 474 100 10 165 300 10 914 200 9 844 600 10 443 600 11 783 600 11 445 800 15 734 100 18 391 000 Goodwill 128 700 3 554 500 3 344 600 2 239 900 2 142 600 2 111 600 2 146 100 2 115 500 2 374 900 2 416 900 Total non-current assets, excl goodwill 2 451 598 15 028 600 13 509 900 13 154 100 11 987 200 12 555 200 13 929 700 13 561 300 18 109 000 20 807 900 Current assets Biological assets 1 060 300 6 311 700 5 553 900 5 620 600 5 351 100 7 278 100 6 285 200 6 207 900 9 536 600 10 014 000 Inventory 73 800 955 700 917 400 1 074 500 742 700 775 800 783 000 819 700 1 751 100 2 400 800 Trade receivables 334 600 2 443 700 1 883 400 1 903 400 1 672 100 1 844 900 1 914 900 1 782 000 3 191 400 3 360 200 Other receivables 80 900 211 400 667 500 532 400 551 600 814 700 609 800 592 700 1 086 500 1 110 500 Total current assets 1 549 600 9 922 500 9 022 200 9 130 900 8 317 500 10 713 500 9 592 900 9 402 300 15 565 600 16 885 500 Non-interest bearing debt Trade payables 222 600 1 787 400 1 349 700 1 729 200 1 339 800 1 450 200 1 481 800 1 452 500 2 232 600 2 039 200 Current tax liabilities - - - 69 900 50 800 49 700 86 600 26 200 252 600 525 200 Other current liabilities 265 700 763 700 907 100 2 349 900 1 048 600 1 112 200 1 180 300 1 475 300 1 967 700 3 112 300 Total non-interest bearing debt, excl deferred tax 488 300 2 551 100 2 256 800 4 149 000 2 439 200 2 612 100 2 748 700 2 954 000 4 452 900 5 676 700 Deferred tax liabilities 84 400 1 866 800 1 199 700 732 900 1 142 600 2 237 900 2 351 900 2 543 700 3 365 000 3 568 900 Total non-interest bearing debt, incl deferred tax 572 700 4 417 900 3 456 500 4 881 900 3 581 800 4 850 000 5 100 600 5 497 700 7 817 900 9 245 600 Net Working capital 1 061 300 7 371 400 6 765 400 4 981 900 5 878 300 8 101 400 6 844 200 6 448 300 11 112 700 11 208 800 Invested Capital. Excl goodwill 3 299 798 16 978 700 15 731 000 15 163 200 14 580 300 16 307 100 16 275 900 15 350 400 23 481 800 26 030 900 Goodwill 128 700 3 554 500 3 344 600 2 239 900 2 142 600 2 111 600 2 146 100 2 115 500 2 374 900 2 416 900 Invested Capital. incl goodwill 3 428 498 20 533 200 19 075 600 17 403 100 16 722 900 18 418 700 18 422 000 17 465 900 25 856 700 28 447 800 Equity and debt (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Equity 1 778 300 13 542 200 12 484 000 9 624 600 11 460 500 12 570 700 10 842 200 11 688 700 16 346 300 14 718 200 Net interest bearing debt Non-current interest-bearing debt 1 610 500 7 956 000 5 856 900 6 747 700 5 116 900 5 107 300 6 589 400 5 338 500 7 710 200 10 669 100 Current interest-bearing debt 185 400 1 625 100 1 249 200 1 365 500 130 300 429 700 157 000 377 800 686 700 7 000 Other non-current liabilities 10 800 202 600 136 400 116 800 99 800 571 100 99 400 414 700 976 100 2 334 400 Liabilities, Capitalized leases - - - - 206 400 183 000 1 105 200 990 000 1 744 200 2 312 400 Liabilities held for sale - 113 900 - - - - - - 190 500 - Interest bearing-debt 1 806 700 9 897 600 7 242 500 8 230 000 5 553 400 6 291 100 7 951 000 7 121 000 11 307 700 15 322 900 Securities Cash and cash equivalents 152 700 2 182 500 362 600 372 600 172 200 318 900 279 100 335 200 606 200 1 408 200 Other shares 3 802 84 100 288 300 78 900 118 800 124 200 92 100 1 008 600 132 100 166 100 Assets held for sale - 640 000 - - - - - - 1 059 000 19 000 Interest bearing assets 156 502 2 906 600 650 900 451 500 291 000 443 100 371 200 1 343 800 1 797 300 1 593 300 Net interest-bearing debt (NIBD) 1 650 198 6 991 000 6 591 600 7 778 500 5 262 400 5 848 000 7 579 800 5 777 200 9 510 400 13 729 600 Invested capital (financing) 3 428 498 20 533 200 19 075 600 17 403 100 16 722 900 18 418 700 18 422 000 17 465 900 25 856 700 28 447 800 135

SalMar Reformulated Income Statement Adjustments made due to operating leases 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net operating lease - - 5 328 5 444 6 263 11 529 34 921 39 648 43 122 6 255 Interest - - 1 758 1 797 2 067 3 805 11 524 13 084 14 230 2 064 Depreciation - - 3 570 3 647 4 196 7 724 23 397 26 564 28 892 4 191 Multiplier - - 6 6 66 6 6 6 6 6 Assets and NIBD - - 31 968 32 664 413 358 69 174 209 526 237 888 258 732 37 530 Income statement (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenue Operating revenues 866 584 1 240 668 1 665 530 1 704 242 2 376 262 3 399 868 3 800 204 4 180 414 6 228 305 7 160 010 other revenues 4 867 7 896 12 157 10 014 1 042 29 564 33 299 24 377 17 555 25 877 Total revenues 871 451 1 248 564 1 677 687 1 714 256 2 377 304 3 429 432 3 833 503 4 204 791 6 245 860 7 185 887 Income from associated companies 73 711 91 752 31 600 12 248 56 769 147 365 97 999 93 909 157 980 96 136 Total revenues including income from associates 945 162 1 340 316 1 709 287 1 726 504 2 434 073 3 576 797 3 931 502 4 298 700 6 403 840 7 282 023 Operating costs Cost of materials -456 871-643 547-836 652-922 016-1 162 445-1 898 698-2 373 168-2 715 056-3 376 109-3 337 411 Excess value of inventory from acquisitions - -8 617-17 641-9 303 - -33 587-20 259 - - - Salaries and other personnel costs -119 766-131 913-217 808-240 393-265 517-313 290-391 745-483 215-623 053-710 430 Other operating costs, adj -85 220-110 851-185 942-248 257-305 710-505 538-670 970-846 335-1 043 177-1 136 698 Change in inventories 27 362 131 612 47 750 103 844 25 567 401 629 395 900 390 297 324 914 162 119 Total operating costs, adj -634 495-763 316-1 210 293-1 316 125-1 708 105-2 349 484-3 060 242-3 654 309-4 717 425-5 022 420 EBITDA, adj 310 667 577 000 498 994 410 379 725 968 1 227 313 871 260 644 391 1 686 415 2 259 603 Depreciation, adj -27 267-37 874-54 241-58 872-70 774-101 686-155 397-196 185-249 712-279 956 EBIT, adj 283 400 539 126 444 753 351 507 655 194 1 125 627 715 863 448 206 1 436 703 1 979 647 Tax on operating profit -59 458-123 484-119 613-98 658-168 646-270 221-58 463-93 590-259 053-502 391 Net operating profit after tax (NOPAT) 223 942 415 642 325 140 252 849 486 548 855 406 657 399 354 616 1 177 650 1 477 256 Non-Operating items 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net financial items -4 997-25 484-55 969-82 012-2 801-40 394-115 151-124 264 214 666-113 994 Interest in capital lease - - -1 758-1 797-2 067-3 805-11 524-13 084-14 230-2 064 Tax shield net financial items 1 048 5 837 15 525 23 523 1 253 10 610 10 345 28 680-36 141 29 453 Net financial expenses after tax -3 949-19 647-40 444-58 489-1 548-29 784-104 806-95 584 178 525-84 541 Impairment loss Adjustment of biomass to fair value 40 785 63 676 94 234-32 996-4 624 184 658-368 098 290 417 528 176-232 349 Non-recurring gains on acquisitions - - - - - - - 62 390 161 755 - Onerous contracts - - - - - -3 635 - - - - Particular biological events - - - - - - -60 070-54 614 - - Write-downs of PP&E - - - - -11 600-1 668-543 -547-5 000-2 399 Special items after tax 32 228 49 091 68 891-23 735-12 048 136 299-393 699 235 494 561 430-175 174 Net profit 252 222 445 087 351 829 168 828 470 885 958 116 147 371 481 442 1 903 375 1 215 477 Tax 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Tax on EBT 66 966 132 231 129 431 65 874 163 217 302 667 13 106 127 062 418 695 413 364 EBT 319 187 577 317 481 260 234 702 634 103 1 260 785 160 478 608 504 2 322 071 1 628 841 Effective tax rate 21,0 % 22,9 % 26,9 % 28,1 % 25,7 % 24,0 % 8,2 % 20,9 % 18,0 % 25,4 % 136

SalMar Reformulated Balance Sheet Balance (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Non-current assets Licenses and rights 222 070 711 503 845 178 914 116 935 916 1 406 483 1 483 752 1 702 152 2 030 710 2 451 271 Land, building & other real property 35 038 50 674 58 342 66 864 102 624 179 364 206 409 233 732 473 408 489 496 Plant, equipment & operating consumables 119 600 224 681 273 569 319 847 403 979 636 720 845 581 947 824 1 248 820 1 336 126 non-current assets, capitalized leases - - 31 968 32 664 413 358 69 174 209 526 237 888 258 732 37 530 Vessels, vehicles, etc 7 483 31 254 16 311 29 374 26 684 55 951 74 455 87 247 137 096 191 953 Other receivables 20 370 9 317 5 316 5 485 12 720 12 276 4 609 4 029 5 225 13 403 Investments in associates 339 035 261 790 258 203 257 615 268 508 866 809 918 868 948 575 402 338 523 711 Total non-current assets, excl goodwill 743 596 1 289 219 1 488 887 1 625 965 2 163 789 3 226 777 3 743 200 4 161 447 4 556 329 5 043 490 Goodwill 5 823 56 155 197 965 196 932 205 458 306 999 433 348 433 348 433 348 447 372 Total non-current assets, incl goodwill 749 419 1 345 374 1 686 852 1 822 897 2 369 247 3 533 776 4 176 548 4 594 795 4 989 677 5 490 862 Current assets Biological assets 344 319 701 017 905 675 971 454 1 011 518 1 580 934 1 420 788 1 986 213 3 077 150 3 114 684 Other inventory 19 718 53 398 63 979 97 768 103 176 128 973 227 935 303 682 171 539 206 454 Trade receivables 72 629 110 156 147 193 148 596 252 155 409 707 505 280 660 944 662 149 888 219 Other current receivables 14 082 51 249 37 785 33 604 73 163 136 266 144 993 245 501 217 584 292 644 Parent company receivables - 295 165 552 84 - - - - - Total current assets 450 748 916 115 1 154 797 1 251 974 1 440 096 2 255 880 2 298 996 3 196 340 4 128 422 4 502 001 Non-interest bearing debt Trade payables 110 995 148 380 98 713 133 022 204 394 351 042 412 802 762 765 515 856 409 485 Tax payable 55 350 79 007 89 867 46 271 146 293 148 088 66 399 7 008 25 843 321 839 Public charges payable - 11 364 22 076 19 137 19 710 48 023 52 980 43 192 93 532 143 757 Other current liabilities 22 630 33 860 44 652 59 837 43 627 106 845 126 195 153 515 192 556 381 226 Total-non interest bearing debt, excl deferred tax 188 975 272 611 255 308 258 267 414 024 653 998 658 376 966 480 827 787 1 256 307 Deferred tax 127 075 336 102 460 067 481 813 498 508 787 188 738 475 872 398 1 199 557 1 262 594 Total-non interest bearing debt, incl deferred tax 316 050 608 713 715 375 740 080 912 532 1 441 186 1 396 851 1 838 878 2 027 344 2 518 901 Net operating working capital 261 773 643 504 899 489 993 707 1 026 072 1 601 882 1 640 620 2 229 860 3 300 635 3 245 694 Invested Capital, excl goodwill 878 294 1 596 621 1 928 309 2 137 859 2 691 353 4 041 471 4 645 345 5 518 909 6 657 407 7 026 590 Goodwill 5 823 56 155 197 965 196 932 205 458 306 999 433 348 433 348 433 348 447 372 Invested Capital, incl goodwill 884 117 1 652 776 2 126 274 2 334 791 2 896 811 4 348 470 5 078 693 5 952 257 7 090 755 7 473 962 Equity and debt (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Equity 407 585 885 214 1 287 326 1 315 112 1 699 806 2 469 367 2 214 610 2 967 713 5 060 784 5 137 277 Net-interest bearing debt Debt to credit institutions 82 785 149 474 88 394 183 999 118 073 51 431 501 754 596 288 397 186 276 667 Debt to credit institutions 283 290 525 498 687 336 758 171 746 071 1 760 567 2 028 537 2 098 240 1 974 521 1 780 174 Leasing liabilities and other non-current liabilities 71 808 97 239 77 319 65 764 68 070 108 606 173 460 125 188 471 716 411 388 Pension liabilities 13 447 3 364 4 507 5 234 5 786 1 714 1 212 528 - - non-current liabilities, capitalized leases - - 31 968 32 664 413 358 69 174 209 526 237 888 258 732 37 530 Debt to parent company 28 693 - - - - - - - - - Interest bearing debt 480 023 775 575 889 524 1 045 832 1 351 358 1 991 492 2 914 489 3 058 132 3 102 155 2 505 759 Securities Investments in shares & other securities 527 762 1 001 975 1 025 1 426 762 15 760 384 519 Pension fund assets - 301 1 766 1 637 4 904 3 901 2 023 2 492 802 1 592 Bank deposits, cash & cash equivalents 2 964 6 950 47 809 23 541 148 424 107 062 47 621 55 336 1 070 998 166 963 Interest bearing assets 3 491 8 013 50 576 26 153 154 353 112 389 50 406 73 588 1 072 184 169 074 Net interest-bearing debt 476 532 767 562 838 948 1 019 679 1 197 005 1 879 103 2 864 083 2 984 544 2 029 971 2 336 685 Invested capital 884 117 1 652 776 2 126 274 2 334 791 2 896 811 4 348 470 5 078 693 5 952 257 7 090 755 7 473 962 137

Grieg Seafood Reformulated Income Statement Adjustments made due to operating leases 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net operating lease 6110 14729 2851 3194 8853 11270 13237 26395 Interest 2 016 4 861 941 1 054 2 921 3 719 4 368 8 710 Depreciation 4 094 9 868 1 910 2 140 5 932 7 551 8 869 17 685 Multiplier 6 6 6 6 6 6 6 6 Assets and NIBD 36660 88374 17106 19164 53118 67620 79422 158370 Income statement (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenue Operating revenues 408 097 535 756 1 021 810 1 477 029 1 612 619 2 446 490 2 046 991 2 050 065 2 404 215 2 665 284 other revenues 11 283 7 704 46 542 10 474 8 826 9 398 16 769 28 164 20 827 73 758 Total revenues 419 380 543 460 1 068 352 1 487 503 1 621 445 2 455 888 2 063 760 2 078 229 2 425 042 2 739 042 Income from associated companies -2 097-66 -1 897 700 1 985 12 337 38 869 11 831 7 889 12 867 Total revenues including income from associates 417 283 543 394 1 066 455 1 488 203 1 623 430 2 468 225 2 102 629 2 090 060 2 432 931 2 751 909 Operating costs Cost of materials -226 204-306 582-746 174-903 678-900 581-932 118-889 677-1 202 314-968 978-1 153 526 Salaries and other personnel costs -39 030-53 696-136 246-165 148-193 300-238 409-238 382-276 103-302 223-339 592 Other operating costs, adj -63 285-53 890-190 704-317 916-407 690-589 558-594 732-631 104-661 919-748 065 Change in inventories 849 40 497 205 859 51 637 158 085-10 412 - - - - Total operating costs -327 670-373 671-867 265-1 335 105-1 343 486-1 770 497-1 722 791-2 109 521-1 933 120-2 241 183 EBITDA, adj 89 613 169 723 199 190 153 098 279 944 697 728 379 838-19 461 499 811 510 726 Depreciation and amortization, adj -38 696-44 147-69 547-100 654-119 672-117 434-134 274-153 794-127 168-122 924 EBIT, adj 50 917 125 576 129 643 52 444 160 272 580 294 245 564-173 255 372 643 387 802 Tax on operation profit -14 325-39 911 58 153-11 568-43 733-153 385-90 647 47 235-77 920-54 970 Net operating profit after tax (NOPAT) 36 592 85 665 187 796 40 877 116 539 426 909 154 917-126 020 294 723 332 832 Non-Operating items 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net financial items -14 271-28 937-39 327-233 965 46 727 2 793-30 822-108 347-73 056-55 722 Interes capitalized leases - - -2 016-4 861-941 -1 054-2 921-3 719-4 368-8 710 Tax shield net financial items 4 015 9 197-18 545 52 677-12 494-460 12 456 30 553 16 189 9 133 Net financial expenses after tax -10 256-19 740-57 872-181 288 34 233 2 333-18 366-77 794-56 867-46 589 Impairment loss / Reversal - - - -200 000-72 385 - - - - Adjustment of biomass to fair value 22 693 42 367-44 075-35 747 115 276 207 629-395 180 98 063 267 450-127 108 Special items after tax 16 309 28 902-63 846-183 749 83 821 206 000-249 305 71 328 211 526-109 091 Net profit 42 645 94 827 52 202-344 404 230 874 631 040-123 159-147 190 430 986 138 086 tax 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 reported tax 16 694 44 179-16 165-97 461 86 640 226 727-72 064-55 170 113 945 22 806 Profir before tax 59 339 139 006 36 037-441 865 317 514 857 767-195 223-202 360 544 931 160 892 Effective tax rate 28,13 % 31,78 % -44,86 % 22,06 % 27,29 % 26,43 % 36,91 % 27,26 % 20,91 % 14,17 % 138

Grieg Seafood Reformulated Balance Sheet Balance (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Non-current assets Licenses and rights 185 902 445 117 849 838 831 921 818 340 926 170 987 596 976 740 994 066 1 066 184 Other intangible assets - - - 8 205 5 578 3 160 4 618 3 800 4 545 11 517 Property, plant and equipment 185 372 300 629 639 092 794 346 819 110 923 546 1 126 699 1 141 317 1 204 207 1 424 562 Investments in associated companies and joint ventures 13 720 10 729 10 879 11 579 13 619 33 456 37 387 49 229 41 190 41 937 Non-current assets, capitalized leases - - 36 660 88 374 17 106 19 164 53 118 67 620 79 422 158 370 Other non-current receivables - 12 667 10 275 1 790-1 958 311 53 255 - Total non-current assets 384 994 769 142 1 546 744 1 736 215 1 673 753 1 907 454 2 209 729 2 238 759 2 323 685 2 702 570 Goodwill 16 063 105 556 138 661 43 616 87 583 90 540 105 373 105 108 107 310 108 708 Total non-current assets 401 057 874 698 1 685 405 1 779 831 1 761 336 1 997 994 2 315 102 2 343 867 2 430 995 2 811 278 Current assets Biological assets 301 467 551 637 1 067 574 1 073 341 1 367 061 1 564 041 1 404 934 1 310 142 1 766 332 1 844 097 Inventories 7 812 17 091 34 927 44 592 49 180 58 409 67 355 65 692 74 015 88 250 Accounts receivable 30 550 60 589 111 893 157 876 188 052 265 350 223 682 124 657 177 814 254 043 Other current receivables 44 018 34 073 82 578 48 488 57 051 43 265 64 581 51 299 54 015 57 287 Total current assets 383 847 663 390 1 296 972 1 324 297 1 661 344 1 931 065 1 760 552 1 551 790 2 072 176 2 243 677 Non interest-bearing debt Accounts payable 60 571 63 703 197 356 214 687 233 443 253 305 303 196 246 119 317 753 300 521 Tax payable - 193 9 402 - - - - - 1 471 50 645 Accrued salary expense and public tax payable - 8 436 8 619 13 611 13 869 25 104 22 514 19 720 21 731 13 013 Other current liabilities 27 409 11 281 25 535 23 702 72 400 41 674 48 452 53 982 54 761 109 803 Derivatives and other financial instruments - - 50 122 532 9 672 1 605 7 887 13 805 11 631 23 475 Total non-interest bearing debt, excl deferred tax 87 980 83 613 240 962 374 532 329 384 321 688 382 049 333 626 407 347 497 457 Deferred tax liabilities 46 715 206 567 281 294 207 020 331 995 531 498 486 702 426 781 557 350 559 542 Total non-interest bearing debt, incl deferred tax 134 695 290 180 522 256 581 552 661 379 853 186 868 751 760 407 964 697 1 056 999 Net operating working capital 295 867 579 777 1 056 010 949 765 1 331 960 1 609 377 1 378 503 1 218 164 1 664 829 1 746 220 Invested capital, excl goodwill 634 146 1 142 352 2 321 460 2 478 960 2 673 718 2 985 333 3 101 530 3 030 142 3 431 164 3 889 248 goodwill 16 063 105 556 138 661 43 616 87 583 90 540 105 373 105 108 107 310 108 708 Invested capital, incl goodwill 650 209 1 247 908 2 460 121 2 522 576 2 761 301 3 075 873 3 206 903 3 135 250 3 538 474 3 997 956 Equity and debt (1000 NOK) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Equity 185 758 579 255 1 266 083 928 603 1 374 421 1 982 405 1 690 150 1 513 230 1 988 557 2 221 919 Net interest-bearing debt Loan - - 9 800 13 517 13 548 14 581 - - 850 646 958 828 Other long-term borrowings 373 195 427 730 563 484 8 065 711 419 646 686 613 673 975 844 24 056 23 640 Financial leasing liabilities - 72 197 123 352 213 117 198 167 168 856 179 670 156 150 170 251 236 430 Other non-current liabilities - 1 962 19 096 5 882 691 3 292 - - - - Bank overdraft - 175 354 337 957 - - - - - - - Short-term loan facilities 133 439 - - 496 702 482 989 260 000 700 000 500 000 425 000 - Current portion of long-term borrowings - 26 115 76 184 807 827 85 295 79 000 79 983 109 542 111 060 487 664 Current portion of financial leasing liabilities - 19 034 52 498 35 305 37 383 41 726 44 662 44 730 46 149 53 231 Pension obligations and cash-settled options 3 368 3 523 4 369 4 161 3 278 7 896 1 751 10 377 610 2 532 non-current liability, Capitalized leases - 36 660 88 374 17 106 19 164 53 118 67 620 79 422 158 370 Cash-settled share options - - - - - - - - 9 567 929 Interest bearing debt 510 002 725 915 1 223 400 1 672 950 1 549 876 1 241 201 1 672 857 1 864 263 1 716 761 1 921 624 Securities Derivatives and other financial instruments - - 1 991 8 243 20 350-1 178-518 - Cash and cash equivalents 9 728 12 691 24 318 68 146 139 778 143 727 152 623 239 886 163 914 144 002 Available-for-sale financial assets 35 823 40 700 156 178 945 557 1 307 1 337 1 392 1 518 Loans to associated companies - 3 871 2 897 2 410 1 923 3 449 996 1 020 1 020 67 Interest-bearing assets 45 551 57 262 29 362 78 977 162 996 147 733 156 104 242 243 166 844 145 587 Net interest-bearing debt 464 451 668 653 1 194 038 1 593 973 1 386 880 1 093 468 1 516 753 1 622 020 1 549 917 1 776 037 Invested capital (financing) 650 209 1 247 908 2 460 121 2 522 576 2 761 301 3 075 873 3 206 903 3 135 250 3 538 474 3 997 956 139

Appendix 3.2 DuPont structure with formulas Source: Own creation / Petersen & Plenborg (2012) ROE ROIC + FGEAR ROIC NOPAT Invested Capital Profit Margin Turnover-ratio FGEAR SPREAD EBIT Gross income Gross income Invested Capital NIBD Equity (ROIC r) 140

Appendix 3.3 Index- and common size analysis Source: Own creation / Annual Reports (2006-2014) Index analysis LSG income statement: Index LSG 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenue Operating revenues 100 140 157 151 186 221 229 227 268 313 Other revenues 100 218 Total revenues 100 140 157 151 186 221 229 227 269 316 Income from associated companies 100 167 46 18 81 158 26 32 249 119 Total revenues including income from associates 100 140 155 148 184 220 225 223 269 313 Operating costs Cost of materials 100 126 144 137 159 168 190 200 216 260 Salaries and other personnel costs 100 163 236 270 281 316 394 420 445 517 Other operating costs 100 179 246 302 306 361 448 446 524 659 Change in inventories 100 77-75 180 33 146 253 Total operating costs 100 131 156 150 171 192 208 226 241 285 EBITDA 100 225 144 137 305 483 377 200 533 564 Depreciation 100 176 319 409 423 456 564 605 637 766 EBIT 100 231 120 100 288 486 351 145 519 536 Tax on operation profit 100 248 130 100 335 571 457 175 554 548 Net operating profit after tax (NOPAT) 100 227 118 100 275 462 320 136 509 533 MHG income statement: Index MHG 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenue Operating revenue 100 376 939 898 974 1018 1075 1027 1277 1685 Other revenues 100 51 534 Total Revenue 100 376 939 898 974 1018 1075 1030 1279 1701 Income from associated companies 100 1693 4757 414 4964 14429-607 6307 15843 10679 Total revenues including income from associates 100 377 942 898 978 1030 1073 1035 1292 1709 Operating costs Cost of materials 100 367 1013 972 979 866 935 1076 1113 1522 Salary and personnel expenses 100 329 849 839 850 863 854 948 1048 1302 Other operating expenses, adj 100 441 660 705 715 720 950 1011 1159 1500 Change in inventory and biological assets, at cost 100 411-34 64 0 0 0 0 0 0 Total operating costs 100 366 1028 993 1009 930 1015 1148 1220 1627 EBITDA, adj 100 424 559 473 838 1478 1330 532 1616 2072 Depreciation and amortization, adj 100 220 569 493 511 484 568 566 688 881 EBIT, adj 100 631 549 453 1170 2488 2104 497 2558 3284 Tax on operational profit 100-17615 15898 2197 9762 25879 15411 9175 29382 64240 Net operating profit after tax (NOPAT) 100 1115 141 406 942 1867 1751 267 1846 1666 141

SALM income statement: Index SALM 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenue Operating revenues 100 143 192 197 274 392 439 482 719 826 other revenues 100 162 250 206 21 607 684 501 361 532 Total revenues 100 143 193 197 273 394 440 483 717 825 Income from associated companies 100 124 43 17 77 200 133 127 214 130 Total revenues including income from associates 100 142 181 183 258 378 416 455 678 770 Operating costs Cost of materials 100 141 183 202 254 416 519 594 739 730 Excess value of inventory from acquisitions 100 100 205 108 0 390 235 0 0 0 Salaries and other personnel costs 100 110 182 201 222 262 327 403 520 593 Other operating costs, adj 100 130 218 291 359 593 787 993 1224 1334 Change in inventories 100 481 175 380 93 1468 1447 1426 1187 592 Total operating costs, adj 100 120 191 207 269 370 482 576 743 792 100 EBITDA, adj 100 186 161 132 234 395 280 207 543 727 Depreciation, adj 100 139 199 216 260 373 570 719 916 1027 EBIT, adj 100 190 157 124 231 397 253 158 507 699 Tax on operating profit 100 208 201 166 284 454 98 157 436 845 Net operating profit after tax (NOPAT) 100 186 145 113 217 382 294 158 526 660 GSF income statement: index GSF 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenue Operating revenues 100 131 250 362 395 599 502 502 589 653 other revenues 100 68 412 93 78 83 149 250 185 654 Total revenues 100 130 255 355 387 586 492 496 578 653 Income from associated companies 100 3 90-33 -95-588 -1854-564 -376-614 Total revenues including income from associates 100 130 256 357 389 591 504 501 583 659 Operating costs Cost of materials 100 136 330 399 398 412 393 532 428 510 Salaries and other personnel costs 100 138 349 423 495 611 611 707 774 870 Other operating costs, adj 100 85 301 502 644 932 940 997 1046 1182 Change in inventories 100 4770 24247 6082 18620-1226 0 0 0 0 Total operating costs 100 114 265 407 410 540 526 644 590 684 EBITDA, adj 100 189 222 171 312 779 424-22 558 570 Depreciation and amortization, adj 100 114 180 260 309 303 347 397 329 318 EBIT, adj 100 247 255 103 315 1140 482-340 732 762 Tax on operation profit 100 279-406 81 305 1071 633-330 544 384 Net operating profit after tax (NOPAT) 100 234 513 112 318 1167 423-344 805 910 142

LSG balance: Balance 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Non-current assets Deferred tax assets 100 83 156 361 134 420 Licenses and rights 100 247 382 417 417 637 641 640 640 695 Buildings, real estate, operating accessories 100 244 403 455 430 557 645 735 835 940 Shares in associates 100 92 86 83 81 101 98 98 219 169 Non-current receivables 100 15 42 387 736 501 521 531 1 614 1 990 Total non-current assets, exl goodwill 100 190 281 308 301 419 447 476 550 587 Goodwill 100 861 1 226 1 240 1 241 1 394 1 410 1 482 1 493 1 548 Total non-current assets, incl goodwill 100 274 401 426 420 542 568 603 669 708 Current assets Biological assets 100 194 275 309 342 499 437 502 687 678 Other inventories 100 199 278 234 248 305 344 342 376 551 Trade receivables 100 127 116 130 147 170 157 167 250 240 Other receivables 100 204 265 192 157 212 179 240 381 364 Total current assets (operating) 100 164 203 215 236 318 287 323 447 451 Non-interest bearing debt Trade payables 100 126 136 146 165 171 189 222 284 282 Public duties payables 100 271 310 402 457 610 512 549 851 575 Taxes payable 100 799 397 87 487 2 058 1 677 463 1 668 1 745 Other current liabilities 100 160 133 173 202 272 240 194 257 348 Total non-interest bearing debt, excl deferred tax 100 162 149 156 192 274 263 232 342 358 Deferred tax liabilities 100 285 406 423 527 796 684 777 939 967 Total non-interest bearing debt, incl deferred tax 100 190 209 218 270 395 361 358 480 499 Net working capital 100 166 238 254 264 348 304 383 517 513 Invested capital, excl goodwill 100 168 247 269 260 345 350 398 494 511 Goodwill 100 861 1 226 1 240 1 241 1 394 1 410 1 482 1 493 1 548 Invested capital, incl goodwill 100 223 324 346 337 428 434 484 573 593 Equity and Debt 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total equity 100 180 290 289 330 460 445 458 580 621 Net interest bearing debt Long-term interest-bearing debt 0 344 376 365 328 485 530 524 514 603 Other long term debt 100 20 32 - - - - Other non-current liabilities 100 625 512 1 841 Pension liabilities 100 212 287 315 358 215 186 182 77 164 Short-term loans 100 291 432 642 493 331 581 696 521 358 Interest bearing-debt 100 332 388 426 365 449 540 567 519 568 Securities Cash and cash equivalents 100 267 281 203 370 710 836 566 456 712 Shares available for sale 100 219 1 010 886 884 879 886 699 212 308 Pension funds 100 147 218 191 - - - - - - Shares and securities 100 - - - - - - - - - Interest-bearing assets 100 265 290 212 375 708 832 565 451 702 Net interest-bearing debt 100 364 436 531 360 322 397 568 552 503 Invested capital (financing) 100 223 324 346 337 428 434 484 573 593 143

MHG balance: Balance (all numbers NOK 1000) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Non-current assets Deferred tax assets 100 4 37 9 19 26 12 29 24 Licenses and rights 100 570 536 556 521 524 537 524 582 628 Propertry, plant and equipment 100 349 323 352 292 322 346 341 554 685 Investments in assoiciated companies 100 936 999 948 960 1253 1152 1195 1662 1805 Other intangible assets 100 2175 1319 1553 1320 1290 1195 1108 1830 1617 Fixed assets, capitalized leases 100 100 89 535 480 845 1120 Other non-current assets 100 0 0 0 0 18 174 494 60 98 Total non-current assets, excl goodwill 100 494 438 470 424 450 507 493 677 792 Goodwill 100 2762 2599 1740 1665 1641 1668 1644 1845 1878 Total non-current assets, excl goodwill 100 613 551 537 489 512 568 553 739 849 Current assets Biological assets 100 595 524 530 505 686 593 585 899 944 Inventory 100 1295 1243 1456 1006 1051 1061 1111 2373 3253 Trade receivables 100 730 563 569 500 551 572 533 954 1004 Other receivables 100 261 825 658 682 1007 754 733 1343 1373 Total current assets 100 640 582 589 537 691 619 607 1004 1090 Non-interest bearing debt Trade payables 100 803 606 777 602 651 666 653 1003 916 Current tax liabilities 100 73 71 124 37 361 751 Other current liabilities 100 287 341 884 395 419 444 555 741 1171 Total non-interest bearing debt, excl deferred tax 100 522 462 850 500 535 563 605 912 1163 Deferred tax liabilities 100 2212 1421 868 1354 2652 2787 3014 3987 4229 Total non-interest bearing debt, incl deferred tax 100 771 604 852 625 847 891 960 1365 1614 Net Working capital 100 695 637 469 554 763 645 608 1047 1056 Invested Capital. Excl goodwill 100 515 477 460 442 494 493 465 712 789 Goodwill 100 2762 2599 1740 1665 1641 1668 1644 1845 1878 Invested Capital. incl goodwill 100 599 556 508 488 537 537 509 754 830 Equity and debt, 1000 NOK 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total Equity 100 762 702 541 644 707 610 657 919 828 Net interest bearing debt Non-current interest-bearing debt 100 494 364 419 318 317 409 331 479 662 Current interest-bearing debt 100 877 674 737 70 232 85 204 370 4 Other non-current liabilities 100 1876 1263 1081 924 5288 920 3840 9038 21615 Liabilities, Capitalized leases 100 89 535 480 845 1120 Liabilities held for sale 100 0 0 0 0 0 0 167 0 Interest bearing-debt 100 548 401 456 307 348 440 394 626 848 Securities Cash and cash equivalents 100 1429 237 244 113 209 183 220 397 922 Other shares 100 2212 7583 2075 3125 3267 2422 26528 3474 4369 Assets held for sale 100 0 0 0 0 0 0 165 3 Interest bearing assets 100 1857 416 288 186 283 237 859 1148 1018 Net interest-bearing debt (NIBD) 100 424 399 471 319 354 459 350 576 832 Invested capital (financing) 100 599 556 508 488 537 537 509 754 830 144

SALM balance: Balance 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Non-current assets Licenses and rights 100 320 381 412 421 633 668 766 914 1104 Land, building & other real property 100 145 167 191 293 512 589 667 1351 1397 Plant, equipment & operating consumables 100 188 229 267 338 532 707 792 1044 1117 non-current assets, capitalized leases 100 102 1293 216 655 744 809 117 Vessels, vehicles, etc 100 418 218 393 357 748 995 1166 1832 2565 Other receivables 100 46 26 27 62 60 23 20 26 66 Investments in associates 100 77 76 76 79 256 271 280 119 154 Total non-current assets, excl goodwill 100 173 200 219 291 434 503 560 613 678 Goodwill 100 964 3400 3382 3528 5272 7442 7442 7442 7683 Total non-current assets, incl goodwill 100 180 225 243 316 472 557 613 666 733 Current assets Biological assets 100 204 263 282 294 459 413 577 894 905 Other inventory 100 271 324 496 523 654 1156 1540 870 1047 Trade receivables 100 152 203 205 347 564 696 910 912 1223 Other current receivables 100 364 268 239 520 968 1030 1743 1545 2078 Parent company receivables 100 56 187 28 0 0 0 0 0 Total current assets 100 203 256 278 319 500 510 709 916 999 Non-interest bearing debt Trade payables 100 134 89 120 184 316 372 687 465 369 Tax payable 100 143 162 84 264 268 120 13 47 581 Public charges payable 100 194 168 173 423 466 380 823 1265 Other current liabilities 100 150 197 264 193 472 558 678 851 1685 Total-non interest bearing debt, excl deferred tax 100 144 135 137 219 346 348 511 438 665 Deferred tax 100 264 362 379 392 619 581 687 944 994 Total-non interest bearing debt, incl deferred tax 100 193 226 234 289 456 442 582 641 797 Net operating working capital 100 246 344 380 392 612 627 852 1261 1240 Invested Capital, excl goodwill 100 182 220 243 306 460 529 628 758 800 Goodwill 100 964 3400 3382 3528 5272 7442 7442 7442 7683 Invested Capital, incl goodwill 100 187 240 264 328 492 574 673 802 845 Equity and debt 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Equity 100 217 316 323 417 606 543 728 1242 1260 Net-interest bearing debt Debt to credit institutions 100 181 107 222 143 62 606 720 480 334 Debt to credit institutions 100 185 243 268 263 621 716 741 697 628 Leasing liabilities and other non-current liabilities 100 135 108 92 95 151 242 174 657 573 Pension liabilities 100 25 34 39 43 13 9 4 0 0 non-current liabilities, capitalized leases 100 102 1293 216 655 744 809 117 Debt to parent company 100 0 0 0 0 0 0 0 0 0 Interest bearing debt 100 162 185 218 282 415 607 637 646 522 Securities Investments in shares & other securities 100 145 190 185 194 271 145 2991 73 98 Pension fund assets 100 587 544 1629 1296 672 828 266 529 Bank deposits, cash & cash equivalents 100 234 1613 794 5008 3612 1607 1867 36134 5633 Interest bearing assets 100 230 1449 749 4421 3219 1444 2108 30713 4843 Net interest-bearing debt 100 161 176 214 251 394 601 626 426 490 Invested capital 100 187 240 264 328 492 574 673 802 845 145

GSF balance: Balance, index 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Non-current assets Licenses and rights 100 239 457 448 440 498 531 525 535 574 Other intangible assets 100 68 39 56 46 55 140 Property, plant and equipment 100 162 345 429 442 498 608 616 650 768 Investments in associated companies and joint ventures 100 78 79 84 99 244 273 359 300 306 Non-current assets, capitalized leases 100 241 47 52 145 184 217 432 Other non-current receivables 100 81 14 0 15 2 0 2 0 Total non-current assets 100 200 402 451 435 495 574 582 604 702 Goodwill 100 657 863 272 545 564 656 654 668 677 Total non-current assets 100 218 420 444 439 498 577 584 606 701 Current assets Biological assets 100 183 354 356 453 519 466 435 586 612 Inventories 100 219 447 571 630 748 862 841 947 1130 Accounts receivable 100 198 366 517 616 869 732 408 582 832 Other current receivables 100 77 188 110 130 98 147 117 123 130 Total current assets 100 173 338 345 433 503 459 404 540 585 Non interest-bearing debt Accounts payable 100 105 326 354 385 418 501 406 525 496 Tax payable 100 4872 0 0 0 0 0 762 26241 Accrued salary expense and public tax payable 100 102 161 164 298 267 234 258 154 Other current liabilities 100 41 93 86 264 152 177 197 200 401 Derivatives and other financial instruments 100 245064 19344 3210 15774 27610 23262 46950 Total non-interest bearing debt, excl deferred tax 100 95 274 426 374 366 434 379 463 565 Deferred tax liabilities 100 442 602 443 711 1138 1042 914 1193 1198 Total non-interest bearing debt, incl deferred tax 100 215 388 432 491 633 645 565 716 785 Net operating working capital 100 196 357 321 450 544 466 412 563 590 Invested capital, excl goodwill 100 180 366 391 422 471 489 478 541 613 goodwill 100 657 863 272 545 564 656 654 668 677 Invested capital, incl goodwill 100 192 378 388 425 473 493 482 544 615 Equity and debt 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Equity 100 312 682 500 740 1067 910 815 1071 1196 Net interest-bearing debt Loan 100 138 138 149 0 0 8680 9784 Other long-term borrowings 100 115 151 2 191 173 164 261 6 6 Financial leasing liabilities 100 171 295 274 234 249 216 236 327 Other non-current liabilities 100 973 300 35 168 0 0 0 0 Bank overdraft 100 193 0 0 0 0 0 0 0 Short-term loan facilities 100 0 0 372 362 195 525 375 318 0 Current portion of long-term borrowings 100 292 3093 327 303 306 419 425 1867 Current portion of financial leasing liabilities 100 276 185 196 219 235 235 242 280 Pension obligations and cash-settled options 100 105 130 124 97 234 52 308 18 75 non-current liability, Capitalized leases 100 241 47 52 145 184 217 432 Cash-settled share options 100 10 Interest bearing debt 100 142 240 328 304 243 328 366 337 377 Securities Derivatives and other financial instruments 100 414 1022 0 59 0 26 0 Cash and cash equivalents 100 130 250 701 1437 1477 1569 2466 1685 1480 Available-for-sale financial assets 100 114 0 0 3 2 4 4 4 4 Loans to associated companies 100 75 62 50 89 26 26 26 2 Interest-bearing assets 100 126 64 173 358 324 343 532 366 320 Net interest-bearing debt 100 144 257 343 299 235 327 349 334 382 Invested capital (financing) 100 192 378 388 425 473 493 482 544 615 146

Common size of invested capital LSG Common Size Analysis 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net Working Capital 46.6 % 34.8 % 34.2 % 34.2 % 36.5 % 37.8 % 32.6 % 36.8 % 42.1 % 40.3 % Licenses and rights 18.2 % 20.2 % 21.4 % 22.0 % 22.5 % 27.1 % 26.8 % 24.0 % 20.3 % 21.3 % Buildings, real estate etc. 16.7 % 18.3 % 20.8 % 22.0 % 21.4 % 21.8 % 24.9 % 25.5 % 24.4 % 26.5 % Goodwill 7.9 % 30.5 % 29.9 % 28.4 % 29.1 % 25.8 % 25.7 % 24.2 % 20.6 % 20.6 % Biological Assets 31.9 % 27.7 % 27.1 % 28.5 % 32.4 % 37.2 % 32.1 % 33.1 % 38.2 % 36.5 % Trade Receivables 35.0 % 19.8 % 12.5 % 13.1 % 15.3 % 13.9 % 12.7 % 12.1 % 15.2 % 14.2 % Trade Payables 21.9 % 12.4 % 9.2 % 9.3 % 10.7 % 8.8 % 9.6 % 10.0 % 10.9 % 10.4 % Invested Capital 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % Source: Authors creation / Annual Reports 2006-2014 MHG Common Size Analysis 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net Working Capital 31.0 % 35.9 % 35.5 % 28.6 % 35.2 % 44.0 % 37.2 % 36.9 % 43.0 % 39.4 % Licenses and rights 30.3 % 28.8 % 29.2 % 33.1 % 32.3 % 29.5 % 30.3 % 31.1 % 23.3 % 22.9 % Buildings, real estate etc. 35.2 % 20.5 % 20.4 % 24.4 % 21.0 % 21.1 % 22.6 % 23.5 % 25.8 % 29.0 % Fixed assets, capitalized leases 0.0 % 0.0 % 0.0 % 0.0 % 1.2 % 1.0 % 6.0 % 5.7 % 6.7 % 8.1 % Goodwill 3.8 % 17.3 % 17.5 % 12.9 % 12.8 % 11.5 % 11.6 % 12.1 % 9.2 % 8.5 % Biological Assets 30.9 % 30.7 % 29.1 % 32.3 % 32.0 % 39.5 % 34.1 % 35.5 % 36.9 % 35.2 % Trade Receivables 9.8 % 11.9 % 9.9 % 10.9 % 10.0 % 10.0 % 10.4 % 10.2 % 12.3 % 11.8 % Trade Payables 6.5 % 8.7 % 7.1 % 9.9 % 8.0 % 7.9 % 8.0 % 8.3 % 8.6 % 7.2 % Invested Capital 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % Source: Authors creation / Annual Reports 2006-2014 SALM Common Size Analysis 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net Working Capital 29.6 % 38.9 % 42.3 % 42.6 % 35.4 % 36.8 % 32.3 % 37.5 % 46.5 % 43.4 % Licenses and rights 25.1 % 43.0 % 39.7 % 39.2 % 32.3 % 32.3 % 29.2 % 28.6 % 28.6 % 32.8 % Buildings, real estate etc. 17.5 % 16.7 % 15.6 % 16.6 % 17.5 % 18.8 % 20.7 % 19.9 % 24.3 % 24.4 % Fixed assets, capitalized leases 0.8 % 1.9 % 2.3 % 2.7 % 15.2 % 2.9 % 5.6 % 5.5 % 5.6 % 3.1 % Goodwill 0.7 % 3.4 % 9.3 % 8.4 % 7.1 % 7.1 % 8.5 % 7.3 % 6.1 % 6.0 % Biological Assets 38.9 % 42.4 % 42.6 % 41.6 % 34.9 % 36.4 % 28.0 % 33.4 % 43.4 % 41.7 % Trade Receivables 8.2 % 6.7 % 6.9 % 6.4 % 8.7 % 9.4 % 9.9 % 11.1 % 9.3 % 11.9 % Trade Payables 12.6 % 9.0 % 4.6 % 5.7 % 7.1 % 8.1 % 8.1 % 12.8 % 7.3 % 5.5 % Invested Capital 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % Source: Authors creation / Annual Reports 2006-2014 GSF Common Size Analysis 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Net Working Capital 45.5 % 46.5 % 42.9 % 37.7 % 48.2 % 52.3 % 43.0 % 38.9 % 47.0 % 43.7 % Licenses and rights 28.6 % 35.7 % 34.5 % 33.0 % 29.6 % 30.1 % 30.8 % 31.2 % 28.1 % 26.7 % Buildings, real estate etc. 28.5 % 24.1 % 26.0 % 31.5 % 29.7 % 30.0 % 35.1 % 36.4 % 34.0 % 35.6 % Fixed assets, capitalized leases 0.0 % 0.0 % 1.5 % 3.5 % 0.6 % 0.6 % 1.7 % 2.2 % 2.2 % 4.0 % Goodwill 2.5 % 8.5 % 5.6 % 1.7 % 3.2 % 2.9 % 3.3 % 3.4 % 3.0 % 2.7 % Biological Assets 46.4 % 44.2 % 43.4 % 42.5 % 49.5 % 50.8 % 43.8 % 41.8 % 49.9 % 46.1 % Trade Receivables 4.7 % 4.9 % 4.5 % 6.3 % 6.8 % 8.6 % 7.0 % 4.0 % 5.0 % 6.4 % Trade Payables 9.3 % 5.1 % 8.0 % 8.5 % 8.5 % 8.2 % 9.5 % 7.9 % 9.0 % 7.5 % Invested Capital 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % Source: Authors creation / Annual Reports 2006-2014 147

Appendix 3.4 - Key financial- and liquidity ratios LSG and peers Lerøy Seafood Average numbers 2006 2007 2008 2009 2010 2011 2012 2013 2014 Invested capital 2 747 211 4 655 536 5 700 861 5 810 025 6 508 064 7 331 417 7 806 225 8 990 074 9 918 348 NIBD 925 946 1 595 755 1 929 268 1 777 726 1 360 799 1 435 397 1 925 364 2 233 623 2 104 076 Equity 1 821 265 3 059 781 3 771 593 4 032 300 5 147 265 5 896 020 5 880 861 6 756 452 7 814 272 Key ratios 2006 2007 2008 2009 2010 2011 2012 2013 2014 Turnover rate invested capital 2,09 1,36 1,06 1,30 1,38 1,25 1,17 1,22 1,29 FGEAR 0,51 0,52 0,51 0,44 0,26 0,24 0,33 0,33 0,27 After tax 2006 2007 2008 2009 2010 2011 2012 2013 2014 Profit margin, after tax 10,8 % 5,1 % 4,5 % 9,9 % 14,0 % 9,5 % 4,1 % 12,6 % 11,3 % ROIC, after tax 22,5 % 6,9 % 4,8 % 12,9 % 19,3 % 11,9 % 4,7 % 15,4 % 14,6 % ROIC*, after tax 22,5 % 6,9 % 4,8 % 12,9 % 19,3 % 11,9 % 4,7 % 15,4 % 14,6 % NBC, after tax 3,3 % 3,3 % 6,0 % 3,6 % 3,6 % 4,0 % 3,6 % 3,5 % 4,4 % ROE, after tax 32,2 % 8,7 % 4,1 % 17,0 % 23,5 % 13,8 % 5,1 % 19,4 % 17,4 % Pre tax 2006 2007 2008 2009 2010 2011 2012 2013 2014 Profit margin, pre tax 14,1 % 6,7 % 5,8 % 13,4 % 19,0 % 13,4 % 5,6 % 16,6 % 14,7 % ROIC pre tax 29,6 % 9,1 % 6,2 % 17,4 % 26,2 % 16,8 % 6,5 % 20,3 % 19,0 % Roic*, pre tax 29,6 % 9,1 % 6,2 % 17,4 % 26,2 % 16,8 % 6,5 % 20,3 % 19,0 % NBC, pre tax 4,4 % 4,4 % 7,8 % 4,8 % 4,9 % 5,7 % 4,9 % 4,6 % 5,7 % ROE, pre tax 42,4 % 11,5 % 5,3 % 23,0 % 31,9 % 19,5 % 7,0 % 25,5 % 22,6 % Liquidity ratios 2006 2007 2008 2009 2010 2011 2012 2013 2014 Current ratio 2,6 3,4 3,5 3,1 2,9 2,8 3,5 3,3 3,2 Quick ratio 1,7 1,9 1,6 1,7 1,8 2,0 1,9 1,5 1,7 Solvency ratio 0,6 0,7 0,6 0,7 0,8 0,8 0,7 0,8 0,8 Interest coverage ratio 20,2 6,1 2,3 11,8 25,8 15,1 5,3 17,9 15,7 Days payables outstanding 42 39 45 43 43 42 46 55 46 Days sales outstanding 60 53 56 49 49 43 48 61 50 Liquidity cycle 2006 2007 2008 2009 2010 2011 2012 2013 2014 NWC 1 318 545 1 889 393 2 015 123 2 096 288 2 755 592 2 406 755 3 032 621 4 099 955 4 065 174 TR NWC 4,26 3,33 3,01 3,57 3,23 3,81 3,00 2,64 3,12 Liquidity cycle 86 110 121 102 113 96 122 138 117 148

Marine Harvest Average numbers 2006 2007 2008 2009 2010 2011 2012 2013 2014 Invested capital 11 980 849 19 804 400 18 239 350 17 063 000 17 570 800 18 420 350 17 943 950 21 661 300 27 152 250 NIBD 4 320 599 6 791 300 7 185 050 6 520 450 5 555 200 6 713 900 6 678 500 7 643 800 11 620 000 Equity 7 660 250 13 013 100 11 054 300 10 542 550 12 015 600 11 706 450 11 265 450 14 017 500 15 532 250 Key ratios 2006 2007 2008 2009 2010 2011 2012 2013 2014 Turnover rate invested capital 0,47 0,71 0,74 0,86 0,88 0,88 0,87 0,90 0,95 FGEAR 0,56 0,52 0,65 0,62 0,46 0,57 0,59 0,55 0,75 After tax 2006 2007 2008 2009 2010 2011 2012 2013 2014 Profit margin, after tax 26,2 % 1,3 % 4,0 % 8,5 % 16,1 % 14,5 % 2,3 % 12,7 % 8,6 % ROIC, after tax 12,4 % 1,0 % 3,0 % 7,4 % 14,2 % 12,7 % 2,0 % 11,4 % 8,2 % ROIC*, after tax 12,4 % 1,0 % 3,0 % 7,4 % 14,2 % 12,7 % 2,0 % 11,4 % 8,2 % NBC, after tax 1,7 % -3,9 % 0,2 % 23,9 % -4,3 % 2,4 % -1,4 % 1,6 % 7,9 % ROE, after tax 18,5 % 3,5 % 4,8 % -2,9 % 22,7 % 18,6 % 4,0 % 16,7 % 8,4 % Pre tax 2006 2007 2008 2009 2010 2011 2012 2013 2014 Profit margin, pre tax 15,2 % 5,3 % 4,6 % 10,9 % 22,0 % 17,9 % 4,4 % 18,0 % 17,5 % ROIC pre tax 7,2 % 3,8 % 3,4 % 9,4 % 19,4 % 15,6 % 3,8 % 16,2 % 16,5 % Roic*, pre tax 7,2 % 3,8 % 3,4 % 9,4 % 19,4 % 15,6 % 3,8 % 16,2 % 16,5 % NBC, pre tax -3,5 % 0,7 % 24,8 % -4,6 % 3,9 % -1,7 % 3,5 % 17,0 % 19,6 % ROE, pre tax 13,3 % 5,4 % -10,5 % 18,0 % 26,5 % 25,5 % 4,0 % 15,7 % 14,3 % Liquidity ratios 2006 2007 2008 2009 2010 2011 2012 2013 2014 Current ratio 3,9 4,0 2,2 3,4 4,1 3,5 3,2 3,5 3,0 Quick ratio 2,2 1,4 0,7 1,0 1,2 1,1 1,3 1,4 1,1 Solvency ratio 0,66 0,65 0,55 0,69 0,68 0,59 0,67 0,63 0,52 Interest coverage ratio -5,7 16,8 0,3-5,3 15,5-25,8 2,9 2,7 2,0 Days payables outstanding 198 54 72 56 68 64 55 82 54 Days sales outstanding 172 66 66 56 64 57 56 81 64 Liquidity cycle 2006 2007 2008 2009 2010 2011 2012 2013 2014 NWC 7 371 400 6 765 400 4 981 900 5 878 300 8 101 400 6 844 200 6 448 300 11 112 700 11 208 800 TR NWC 0,77 2,08 2,71 2,49 1,89 2,36 2,40 1,73 2,28 Liquidity cycle 477 175 135 147 194 155 152 211 160 149

SalMar Average numbers 2006 2007 2008 2009 2010 2011 2012 2013 2014 Invested capital 1 268 447 1 889 525 2 230 533 2 615 801 3 622 641 4 713 582 5 515 475 6 521 506 7 282 359 NIBD 622 047 803 255 929 314 1 108 342 1 538 054 2 371 593 2 924 314 2 507 258 2 183 328 Equity 646 400 1 086 270 1 301 219 1 507 459 2 084 587 2 341 989 2 591 162 4 014 249 5 099 031 Key ratios 2006 2007 2008 2009 2010 2011 2012 2013 2014 Turnover rate invested capital 1,06 0,90 0,77 0,93 0,99 0,83 0,78 0,98 1,00 FGEAR 0,96 0,74 0,71 0,74 0,74 1,01 1,13 0,62 0,43 After tax 2006 2007 2008 2009 2010 2011 2012 2013 2014 Profit margin, after tax 31,0 % 19,0 % 14,6 % 20,0 % 23,9 % 16,7 % 8,2 % 18,4 % 20,3 % ROIC, after tax 32,8 % 17,2 % 11,3 % 18,6 % 23,6 % 13,9 % 6,4 % 18,1 % 20,3 % ROIC*, after tax 32,8 % 17,2 % 11,3 % 18,6 % 23,6 % 13,9 % 6,4 % 18,1 % 20,3 % NBC, after tax 3,2 % 5,0 % 6,3 % 0,1 % 1,9 % 4,4 % 3,3 % -7,1 % 3,9 % ROE, after tax 61,3 % 26,2 % 14,9 % 32,2 % 39,6 % 23,6 % 10,0 % 33,8 % 27,3 % Pre tax 2006 2007 2008 2009 2010 2011 2012 2013 2014 Profit margin, pre tax 40,2 % 26,0 % 20,4 % 26,9 % 31,5 % 18,2 % 10,4 % 22,4 % 27,2 % ROIC pre tax 42,5 % 23,5 % 15,8 % 25,0 % 31,1 % 15,2 % 8,1 % 22,0 % 27,2 % Roic*, pre tax 42,5 % 23,5 % 15,8 % 25,0 % 31,1 % 15,2 % 8,1 % 22,0 % 27,2 % NBC, pre tax 4,1 % 7,2 % 9,0 % 0,4 % 2,9 % 5,3 % 4,7 % -8,0 % 5,3 % ROE, pre tax 79,5 % 35,6 % 20,6 % 43,1 % 51,9 % 25,2 % 12,0 % 40,8 % 36,5 % Liquidity ratios 2006 2007 2008 2009 2010 2011 2012 2013 2014 Current ratio 3,4 4,5 4,8 3,5 3,4 3,5 3,3 5,0 3,6 Quick ratio 0,6 0,9 0,8 1,2 1,0 1,1 1,0 2,4 1,1 Solvency ratio 0,54 0,61 0,56 0,59 0,57 0,44 0,50 0,71 0,7 Interest coverage ratio 21,2 7,7 4,2 134,6 25,5 5,7 3,3-7,2 17,1 Days payables outstanding 84 43 53 64 67 63 103 56 45 Days sales outstanding 47 40 39 50 58 62 79 51 60 Liquidity cycle 2006 2007 2008 2009 2010 2011 2012 2013 2014 NWC 643 504 899 489 993 707 1 026 072 1 601 882 1 640 620 2 229 860 3 300 635 3 245 694 TR NWC 1,94 1,87 1,73 2,32 2,14 2,34 1,89 1,89 2,21 Liquidity cycle 188 196 212 158 170 156 194 193 165 150

Grieg Seafood Average numbers 2006 2007 2008 2009 2010 2011 2012 2013 2014 Invested capital 949 059 1 854 015 2 491 349 2 641 939 2 918 587 3 141 388 3 171 077 3 336 862 3 768 215 NIBD 566 552 931 346 1 394 006 1 490 427 1 240 174 1 305 111 1 569 387 1 585 969 1 662 977 Equity 382 507 922 669 1 097 343 1 151 512 1 678 413 1 836 278 1 601 690 1 750 894 2 105 238 Key ratios 2006 2007 2008 2009 2010 2011 2012 2013 2014 Turnover rate invested capital 0,57 0,58 0,60 0,61 0,85 0,67 0,66 0,73 0,73 FGEAR 1,48 1,01 1,27 1,29 0,74 0,71 0,98 0,91 0,79 After tax 2006 2007 2008 2009 2010 2011 2012 2013 2014 Profit margin, after tax 15,8 % 17,6 % 2,7 % 7,2 % 17,3 % 7,4 % -6,0 % 12,1 % 12,1 % ROIC, after tax 9,0 % 10,1 % 1,6 % 4,4 % 14,6 % 4,9 % -4,0 % 8,8 % 8,8 % ROIC*, after tax 9,0 % 10,1 % 1,6 % 4,4 % 14,6 % 4,9 % -4,0 % 8,8 % 8,8 % NBC, after tax 1,8 % 2,1 % 4,2 % 12,2 % -2,8 % -0,2 % 1,2 % 4,9 % 3,4 % ROE, after tax 19,7 % 18,2 % -1,5 % -5,6 % 27,5 % 8,6 % -9,0 % 12,4 % 13,1 % Pre tax 2006 2007 2008 2009 2010 2011 2012 2013 2014 Profit margin, pre tax 23,1 % 12,2 % 3,5 % 9,9 % 23,5 % 11,7 % -8,3 % 15,3 % 14,1 % ROIC pre tax 13,2 % 7,0 % 2,1 % 6,1 % 19,9 % 7,8 % -5,5 % 11,2 % 10,3 % Roic*, pre tax 13,2 % 7,0 % 2,1 % 6,1 % 19,9 % 7,8 % -5,5 % 11,2 % 10,3 % NBC, pre tax 5,1 % 4,4 % 17,1 % -3,1 % -0,1 % 2,6 % 7,1 % 4,9 % 3,9 % ROE, pre tax 25,3 % 9,6 % -17,0 % 17,9 % 34,7 % 11,5 % -17,8 % 16,9 % 15,4 % Liquidity ratios 2006 2007 2008 2009 2010 2011 2012 2013 2014 Current ratio 7,9 5,4 3,5 5,0 6,0 4,6 4,7 5,1 4,5 Quick ratio 1,8 0,9 0,8 1,2 1,4 1,2 1,3 1,0 0,9 Solvency ratio 0,46 0,51 0,37 0,50 0,64 0,53 0,48 0,56 0,56 Interest coverage ratio 4,3 3,1 0,2-3,5-333,7 7,3-1,5 4,8 6,0 Days payables outstanding 76 97 87 95 99 124 75 120 95 Days sales outstanding 64 69 51 55 46 51 31 35 43 Liquidity cycle 2006 2007 2008 2009 2010 2011 2012 2013 2014 NWC 579 777 1 056 010 949 765 1 331 960 1 609 377 1 378 503 1 218 164 1 664 829 1 746 220 TR NWC 0,94 1,01 1,57 1,22 1,53 1,50 1,71 1,46 1,57 Liquidity cycle 389 361 233 300 239 244 214 251 233 Appendix 3.5 Standard deviation revenues Change in operating revenues 2006 2007 2008 2009 2010 2011 2012 2013 2014 Std dev LSG -2,3 % -6,1 % -7,7 % 5,4 % 10,5 % -11,7 % -11,7 % 25,3 % 6,9 % 0,12 MHG 67,6 % -20,7 % -0,5 % 8,3 % 15,9 % -9,2 % -16,5 % 41,9 % 8,3 % 0,29 GSF -39,2 % 57,0 % 13,1 % 15,9 % 15,2 % -10,6 % -14,0 % 41,4 % -0,6 % 0,29 SALM 13,9 % -7,7 % 0,8 % 17,7 % 39,5 % -15,1 % 11,5 % 32,9 % -6,2 % 0,19 Average 10,0 % 5,6 % 1,4 % 11,8 % 20,2 % -11,6 % -7,7 % 35,4 % 2,1 % 0,25 151

Strategic analysis Appendix 4.1 Porters five forces model 152

Appendix 4.2 Export volumes 2014-2015 from Norway Appendix 4.3 Yearly salmon consumption Source: Pareto Securities, Quarterly Seafood Equity Research April 2014 Forecast 153

Appendix 5.1 - Regression model with supply and European Union GDP growth Source: Kontali Analyse / International Monetary Fund (European GDP) The historical input to the regression is summarized in the figure below. Year Global supply EU GDP (2015 numbers) Price 1995 446 9.516,68 32,95 1996 544 9.708,63 28,72 1997 626 9.969,70 27,86 1998 681 10.261,21 29,07 1999 786 10.562,89 30,38 2000 873 10.977,91 34,73 2001 988 11.229,96 28,11 2002 1057 11.390,21 25,74 2003 1143 11.577,69 23,18 2004 1206 11.881,72 21,73 2005 1249 12.147,64 25,72 2006 1270 12.593,21 32,32 2007 1397 13.014,58 25,76 2008 1492 13.107,50 26,35 2009 1468 12.541,92 30,87 2010 1475 12.798,90 37,26 2011 1644 13.029,15 31,99 2012 2009 12.975,60 26,58 2013 2043 12.990,52 39,59 2014 2227 13.172,00 40,3 Due to uncertainty relating to the development in demand and lack of historical data, we found European GDP as a good indicator of the gross demand for salmon. The regression model have a time series from 1995-2014 with salmon as a dependent variable and global supply of Atlantic salmon and European GDP as explanatory variables. We were not able to get more data, but we characterize the data as sufficient in order to shed light on the correlation between the prices of salmon, global supply and demand. The inputs to the time series are based on different quantities, NOK per kg for the price of salmon, Euro Billions for the GDP in the European Union and tons for the global supply. Hence, in order to make the data comparable then we have transformed each of the series into logarithmic numbers. To generalize the results from our regression model to other periods, then the time series needs to be stationary. 1 If the result of the time series in non-stationarity, the regression analysis will be of little or no use when forecasting the future salmon prices. The time series are stationary if its variance and mean are constant over time and the value of the covariance between the two time periods only depends on the distance between two time periods. 2 Several tests can be used to determine whether a time series is stationary or not, we will use graphical 1 Basic Econometrics, Damodaran N. Gujarati page 741 2 Basic Econometrics, Damodaran N. Gujarati page 740 Year LN growth rates Global EU GDP supply 2015 Price 1996 19,9 % 2,0 % -13,7 % 1997 14,0 % 2,7 % -3,0 % 1998 8,4 % 2,9 % 4,3 % 1999 14,3 % 2,9 % 4,4 % 2000 10,5 % 3,9 % 13,4 % 2001 12,4 % 2,3 % -21,1 % 2002 6,8 % 1,4 % -8,8 % 2003 7,8 % 1,6 % -10,5 % 2004 5,4 % 2,6 % -6,5 % 2005 3,5 % 2,2 % 16,9 % 2006 1,7 % 3,6 % 22,8 % 2007 9,5 % 3,3 % -22,7 % 2008 6,6 % 0,7 % 2,3 % 2009-1,6 % -4,4 % 15,8 % 2010 0,5 % 2,0 % 18,8 % 2011 10,8 % 1,8 % -15,2 % 2012 20,1 % -0,4 % -18,5 % 2013 1,7 % 0,1 % 39,8 % 2014 8,6 % 1,4 % 1,8 % 154

analysis. The pictures below shows the illustrations of the relevant variables, and it can be seen that there is an upward trend among all of the variables suggesting that the mean of the log of variables has been changing. This indicated that the time series are not stationary meaning that the time series have a timevarying mean, variance or both. 8,0 7,5 7,0 6,5 LN Global Supply 6,0 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 LN Global Supply Linear (LN Global Supply) LN EU GDP 9,6 9,5 9,4 9,3 9,2 9,1 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 LN EU GDP Linear (LN EU GDP) LN Price 3,8 3,6 3,4 3,2 3,0 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 LN Price Linear (LN Price) In order to confirm that the time series are stationary, we have calculated the Ln growth between each year. 3 As seen from figure below, our new Ln Growth time series is moving with a constant mean and variance in the start, while it looks very unstable in recent years as seen from the volatility in LN growth Salmon Price. This can be seen by the decrease in supply in 2007-2010 due the ISA virus which decreased 3 Ln Growth1 Ln Growth (T-1) 155

supply in Chile, as well as the large variation in demand. Based on this, we are not very confidence to apply these numbers into our regression model due to the recent volatility. 50,0 % 30,0 % 10,0 % -10,0 % 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014-30,0 % -50,0 % LN Growth Supply LN Growth Euro GDP LN Growth Salmon Price The table below summarizes the results from our regression and these three parameters will be used in our price-equation. Regression Statistics Multiple R 0,685699 R Square 0,470184 Adjusted R Square 0,403956 Standard Error 0,130794 Observations 19 ANOVA df SS MS F Significance F Regression 2 0,242904 0,121452064 7,099568403 0,006209 Residual 16 0,273711 0,017106964 Total 18 0,516616 Coefficients Standard Error t Stat P-value Lower 95%Upper 95%Lower 95,0%Upper 95,0% Intercept 0,170246 0,055511 3,066904759 0,007373419 0,052569 0,287923 0,052569 0,287923 LN growth Supply -1,949 0,530295-3,675316887 0,002046309-3,07318-0,82483-3,07318-0,82483 LN growth EU GDP 0,310308 1,729298 0,179441853 0,859843532-3,35564 3,976256-3,35564 3,976256 Our two explanatory variables have p-values of 0,002 for supply and 0,8598 for European GDP. Hence, according to statistical theory then we should reject a linear relationship between salmon price and European GDP, while we should accept salmon price and supply. Further, the explanatory power of the regression model indicates that 47% of the variation in the salmon price can be explained by the variation in supply and GDP, which we find satisfying. As expected, the parameter of LN growth Supply is negative at -1,9490, which indicates that a increase in supply will have a negative impact on the price of salmon. The EU GDP has a parameter of 0,3103 which indicates that an increase will have a positive impact on the price of salmon. The intercept is the constant in our regression. This leads to the following equation which explains the salmon price growth factor: 156

Salmon price growth factor = 0,1702 + -1,9490 * log (supply growth) + 0,3103 * log (EU GDP growth) The above salmon price equation is still a logarithmic number. In order to get the salmon price back to NOK then the previous periods will be multiplied with e raised to the power of the salmon price growth factor: 2014 2015E 2016E 2017E 2018E 2019E 2020E LN Global Supply 8,62 % 3,92 % 3,92 % 3,92 % 5,83 % 5,83 % 5,83 % LN EU GDP 1,39 % 1,83 % 1,93 % 1,89 % 1,86 % 1,86 % 1,84 % LN Price 0,65 % 9,95 % 9,98 % 9,97 % 6,24 % 6,25 % 6,24 % Price 44,52 49,19 54,34 57,84 61,57 65,53 The results of our forecast can be seen above, and the results gave us unrealistic numbers. However, our analysis is not valid according to the statistical theory since p-value value of EU GDP is rejected. The reason for this may be because the lack of data, the volatility in recent years and the GDP forecasts which is much lower than Kontali and analysts expectations. The p-values would also be lower if we could include other explanatory variables, but there was not possible to find any historical data. Based on these arguments, we conclude that we needed to find other numbers for demand which would give us a more reliable outcome. 157

Appendix 5.2 Supply and Demand regression input Source: Kontali Analyse / Frank Asche Input regression model Year Global supply Global Demand Price Year Global supply Global Demand* Price 2001 988 28,11 2002 7 % 0 % -8 % 2002 1057 0 % 25,74 2003 8 % 12 % -10 % 2003 1143 12 % 23,18 2004 6 % 9 % -6 % 2004 1206 9 % 21,73 2005 4 % 17 % 18 % 2005 1249 17 % 25,72 2006 2 % 22 % 26 % 2006 1270 22 % 32,32 2007 10 % 2 % -20 % 2007 1397 2 % 25,76 2008 7 % 4 % 2 % 2008 1492 4 % 26,35 2009-2 % 10 % 17 % 2009 1468 10 % 30,87 2010 0 % 20 % 21 % 2010 1475 20 % 37,26 2011 11 % 7 % -14 % 2011 1644 7 % 31,99 2012 22 % 9 % -17 % 2012 2009 9 % 26,58 2013 2 % 14 % 49 % 2013 2043 14 % 39,59 2014 9 % 8 % 2 % 2014 2227 8 % 40,3 * Collected from sources Appendix 5.3 Forecast supply and demand Forecast Supply 2015E 2016E 2017E 2018E 2019E 2020E 2021E FondsFinans 3,7 % 0,8 % Pareto 2,0 % 4,0 % 4,0 % 6,0 % 6,0 % 6,0 % 6,0 % Nordea 3,9 % 4,4 % 3,3 % Kontali 3,0 % 3,0 % 3,0 % 3,0 % 3,0 % 3,0 % Average 3,2 % 3,1 % 3,4 % 4,5 % 4,5 % 4,5 % Our estimates 4,0 % 4,0 % 4,0 % 6,0 % 6,0 % 6,0 % 6,0 % Source: Compiled by authors', Fonds finans, Marine Harvest handbook 2014, Nordea markets, Pareto Forecast Demand 2015E 2016E 2017E 2018E 2019E 2020E 2021E FondsFinans 4,4 % 8,6 % pareto* 8 % 8 % 8 % 8 % 8 % 8 % 8 % Nordea 4 % 4 % Kontali** 4,0 % 4,0 % 4,0 % 6,0 % 6,0 % 6,0 % 6,0 % Average 5,2 % 6,2 % 6,0 % 7,0 % 7,0 % 7,0 % 7,0 % Our estimates 5,0 % 8,0 % 6,0 % 6,0 % 6,0 % 6,0 % 6,0 % *Expected demand growth for Norwegian products, **Kontali analyse expects demand to match supply in the future Source: Compiled by authors', Fonds finans, Marine Harvest handbook 2014, Nordea markets, Pareto 158

Appendix 5.4 - Fish pool forward price and eight investments banks salmon price forecast Source: Fish Pool and IntraFish Market estimates 2015E 2016E 2017E 2018E 2019E 2020E Fishpool 41,5 42,9 41,5 35,6 35,6 35,6 Fonds finans 41,0 43,0 ABG Sundal Collier 40,4 42,5 42,5 SEB Enskilda 40,0 40,0 40,0 Handelsbanken 40,0 43,5 43,5 Norne 43,0 45,0 Nordea Markets 39,0 41,0 40,0 Swedbank 42,5 43,6 Pareto 40,9 43,5 44,5 Average 40,9 42,8 42,0 35,6 35,6 35,6 Appendix 5.5 Correlation between spot price and sales premium Source: Annual reports 2005-2014, fishpool Correlation 2006 2007 2008 2009 2010 2011 2012 2013 2014 Spot Price 32,32 25,76 26,35 30,87 37,26 31,99 26,58 39,59 40,30 Premium 2,33 2,75 2,48 2,23 2,04 2,10 2,23 1,88 1,97 Corell -0,85 Appendix 5.6 Growth harvest volumes Harvest volumes 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Average Average LSG period 5 year Volume 52 000 74 500 88 900 92 700 108 500 116 800 136 600 153 400 144 800 158 300 112 650 141 980 Growth 43,3 % 19,3 % 4,3 % 17,0 % 7,6 % 17,0 % 12,3 % -5,6 % 9,3 % 13,8 % 8,1 % Harvest volumes 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Average Average Industry period 5 year Avg volume 37 631 64 903 133 302 134 074 140 337 138 756 160 876 179 577 165 408 195 727 135 059 168 069 Growth 72,5 % 105,4 % 0,6 % 4,7 % -1,1 % 15,9 % 11,6 % -7,9 % 18,3 % 24,4 % 7,4 % 159

Appendix 5.7 - Forecast Assumptions Income statement: 2015E 2016E 2017E 2018E 2019E 2020E 2021E Harvest volume 166 000 177 620 188 277 197 691 205 599 213 823 219 168 Price 41,0 43,0 42,5 38,0 36,0 35,6 35,6 Premium 1,95 1,85 1,90 2,00 2,00 2,00 2,00 Sales price 80,0 79,6 80,8 76,0 72,0 71,2 71,2 Operating revenue 13 271 700 14 129 671 15 203 384 15 024 521 14 803 107 15 224 173 15 604 777 growth 5,5 % 6,5 % 7,6 % -1,2 % -1,5 % 2,8 % 2,5 % Other revenues 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % Income from associated companies 0,40 % 0,40 % 0,40 % 0,40 % 0,40 % 0,40 % 0,40 % Total revenues including income from associates 100,40 % 100,40 % 100,40 % 100,40 % 100,40 % 100,40 % 100,40 % Operating costs Cost of goods sold -64,00 % -63,60 % -63,40 % -63,20 % -63,00 % -63,00 % -63,00 % Salaries and other personnel costs -10,20 % -10,20 % -10,20 % -10,20 % -10,20 % -10,20 % -10,20 % Other operating costs -9,50 % -9,50 % -9,50 % -9,50 % -9,50 % -9,50 % -9,50 % Total operating costs -83,70 % -83,30 % -83,10 % -82,90 % -82,70 % -82,70 % -82,70 % EBITDA Margin 16,70 % 17,10 % 17,30 % 17,50 % 17,70 % 17,70 % 17,70 % Depreciation as a % of PPE -13,80 % -13,80 % -13,80 % -13,80 % -13,80 % -13,80 % -13,80 % EBIT Margin 13,75 % 14,21 % 14,41 % 14,61 % 14,81 % 14,81 % 14,81 % Tax rate -28 % -28 % -28 % -28 % -28 % -28 % -28 % Borrowing cost -5,2 % -5,2 % -5,2 % -5,2 % -5,2 % -5,2 % -5,2 % NOPAT margin 9,9 % 10,3 % 10,4 % 10,6 % 10,7 % 10,7 % 10,7 % 160

Balance sheet: As % of operating revenue 2010 2011 2012 2013 2014 Average 2015E 2016E 2017E 2018E 2019E 2020E 2021E Non-current assets Deferred tax assets 0,04 % 0,07 % 0,24 % 0,11 % 0,34 % 0,16 % 0,2 % 0,2 % 0,2 % 0,2 % 0,2 % 0,2 % 0,2 % Licenses and rights 22,19 % 21,59 % 21,74 % 18,38 % 17,10 % 20,20 % 16,3 % 15,5 % 15,3 % 16,3 % 17,1 % 17,7 % 17,7 % Buildings, real estate, operating accessories 17,85 % 20,01 % 23,01 % 22,08 % 21,28 % 20,85 % 21,0 % 20,5 % 20,5 % 20,5 % 20,5 % 20,5 % 20,5 % Shares in associates 3,81 % 3,59 % 3,64 % 6,83 % 4,51 % 4,47 % 3,8 % 3,8 % 3,8 % 3,8 % 3,8 % 3,8 % 3,8 % Non-current receivables 0,09 % 0,09 % 0,09 % 0,24 % 0,26 % 0,16 % 0,2 % 0,2 % 0,2 % 0,2 % 0,2 % 0,2 % 0,2 % Total non-current assets exl goodwill 43,99 % 45,36 % 48,72 % 47,64 % 43,48 % 45,84 % 41,4 % 40,1 % 40,0 % 40,9 % 41,8 % 42,4 % 42,4 % Goodwill 21,10 % 20,67 % 21,90 % 18,66 % 16,56 % 19,78 % 2.082.706 2.082.706 2.082.706 2.082.706 2.082.706 2.082.706 2.134.774 Total non-current assets incl goodwill 65,09 % 66,03 % 70,61 % 66,30 % 60,04 % 65,61 % 57,1 % 54,9 % 53,8 % 55,1 % 55,9 % 56,1 % 56,1 % Current assets Biological assets 30,45 % 25,84 % 29,93 % 34,63 % 29,27 % 30,02 % 29,5 % 29,5 % 30,0 % 30,4 % 30,7 % 31,0 % 31,0 % Other inventories 3,27 % 3,57 % 3,58 % 3,33 % 4,17 % 3,59 % 3,5 % 3,5 % 3,5 % 3,5 % 3,5 % 3,5 % 3,5 % Trade receivables 11,41 % 10,18 % 10,93 % 13,81 % 11,35 % 11,54 % 11,5 % 11,5 % 11,5 % 11,5 % 11,5 % 11,5 % 11,5 % Other receivables 1,98 % 1,62 % 2,19 % 2,94 % 2,41 % 2,23 % 2,3 % 2,3 % 2,3 % 2,3 % 2,3 % 2,3 % 2,3 % Total current assets 47,11 % 41,21 % 46,64 % 54,70 % 47,20 % 47,37 % 46,8 % 46,8 % 47,3 % 47,7 % 48,0 % 48,3 % 48,3 % Non-interest bearing debt Trade payables 7,2 % 7,7 % 9,1 % 9,8 % 8,4 % 8,4 % 8,4 % 8,4 % 8,4 % 8,4 % 8,4 % 8,4 % 8,4 % Public duties payables 0,8 % 0,7 % 0,7 % 1,0 % 0,6 % 0,8 % 0,8 % 0,8 % 0,8 % 0,8 % 0,8 % 0,8 % 0,8 % Taxes payable 4,4 % 3,5 % 1,0 % 3,0 % 2,7 % 2,9 % 2,9 % 2,9 % 2,9 % 2,9 % 2,9 % 2,9 % 2,9 % Other current liabilities 3,6 % 3,1 % 2,5 % 2,8 % 3,3 % 3,1 % 3,1 % 3,1 % 3,1 % 3,1 % 3,1 % 3,1 % 3,1 % Total non-interest bearing debt excl deferred tax 16,1 % 15,0 % 13,3 % 16,6 % 14,9 % 15,2 % 15,2 % 15,2 % 15,2 % 15,2 % 15,2 % 15,2 % 15,2 % Deferred tax liabilities 14,2 % 11,8 % 13,5 % 13,8 % 12,2 % 13,1 % 0,0 % 0,0 % 0,0 % 0,0 % 0,0 % 0,0 % 0,0 % Total non-interest bearing debt incl deferred tax 30,3 % 26,8 % 26,8 % 30,4 % 27,1 % 28,3 % 15,2 % 15,2 % 15,2 % 15,2 % 15,2 % 15,2 % 15,2 % Net working capital 31,0 % 26,2 % 33,3 % 38,1 % 32,3 % 32,2 % 31,7 % 31,7 % 32,2 % 32,6 % 32,9 % 33,2 % 33,2 % Invested capital exlc goodwill and deferred tax 75,0 % 71,6 % 82,0 % 85,7 % 75,8 % 78,0 % 73,10 % 71,78 % 72,12 % 73,48 % 74,66 % 75,53 % 75,53 % Invested capital inlc goodwill and deferred tax 81,9 % 80,4 % 90,4 % 90,6 % 80,2 % 84,7 % 88,8 % 86,5 % 86,0 % 87,7 % 88,7 % 89,2 % 89,2 % Equity as a % of invested capital 82,33 % 78,53 % 72,47 % 77,42 % 80,10 % 78,17 % 80 % 80 % 80 % 80 % 80 % 80 % 80 % Net interest-bearing debt as % of invested capital 17,67 % 21,47 % 27,53 % 22,58 % 19,90 % 21,83 % 20,0 % 20,0 % 20,0 % 20,0 % 20,0 % 20,0 % 20,0 % Invested capital (financing) 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 161

Appendix 5.8 Forecast Assumptions KG Income statement 2015E 2016E 2017E 2018E 2019E 2020E 2021E Harvest volume 166 000 177 620 188 277 197 691 205 599 213 823 219 168 Price 41,0 43,0 42,5 38,0 36,0 35,6 35,6 Premium 1,95 1,85 1,90 2,00 2,00 2,00 2,00 Sales price 79,95 79,55 80,75 76,00 72,00 71,20 71,20 Operating revenue 13 271 700 14 129 671 15 203 384 15 024 521 14 803 107 15 224 173 15 604 777 growth 2,8 % 20,3 % 4,8 % -1,4 % -1,5 % 2,8 % 2,5 % Other revenues - - - - - - - Income from associated companies 0,3 0,3 0,3 0,3 0,3 0,3 0,3 Total revenues including income from associates 80,3 79,9 81,1 76,3 72,3 71,5 71,5 Operating costs COGS -51,2-50,6-51,2-48,0-45,4-44,9-44,9 Salaries and other personnel costs -8,2-8,1-8,2-7,8-7,3-7,3-7,3 Other operating costs -7,6-7,6-7,7-7,2-6,8-6,8-6,8 Total operating costs -66,9-66,3-67,1-63,0-59,5-58,9-58,9 EBITDA per KG 13,4 13,6 14,0 13,3 12,7 12,6 12,6 Depreciation per KG -2,3-2,3-2,3-2,2-2,0-2,0-2,0 EBIT per KG 11,0 11,4 11,7 11,1 10,7 10,6 10,6 Tax rate -28 % -28 % -28 % -28 % -28 % -28 % -28 % Borrowing cost, pre tax -5,2 % -5,2 % -5,2 % -5,2 % -5,2 % -5,2 % -5,2 % NOPAT pr KG 7,94 8,17 8,41 8,03 7,71 7,62 7,62 162

Balance sheet: Per kilgrom harvested 2010 2011 2012 2013 2014 Average 2015E 2016E 2017E 2018E 2019E 2020E 2021E Non-current assets Deferred tax assets 0,0 0,0 0,1 0,1 0,3 0,1 0,16 0,16 0,16 0,15 0,14 0,14 0,14 Licenses and rights 16,9 14,5 12,9 13,7 13,6 14,3 13,0 12,3 12,2 12,1 12,3 12,6 12,6 Buildings, real estate, operating accessories 13,6 13,4 13,7 16,4 16,9 14,8 16,8 16,3 16,4 15,2 14,8 14,6 14,6 Shares in associates 2,9 2,4 2,2 5,1 3,6 3,2 3,0 3,0 3,0 2,8 2,7 2,7 2,7 Non-current receivables 0,1 0,1 0,1 0,2 0,2 0,1 0,1 0,1 0,1 0,1 0,1 0,1 0,1 Total non-current assets exl goodwill 33,5 30,5 28,9 35,4 34,6 32,6 33,1 31,9 31,9 30,3 30,1 30,2 30,2 Goodwill 16,1 13,9 13,0 13,9 13,2 14,0 2.082.706,0 2.082.706,0 2.082.706,0 2.082.706,0 2.082.706,0 2.082.706,0 2.134.773,7 Total non-current assets incl goodwill 49,5 44,4 41,9 49,3 47,7 46,6 45,7 43,6 43,0 40,9 40,2 39,9 39,9 Current assets Biological assets 23,2 17,4 17,8 25,7 23,3 21,5 23,6 23,5 24,0 22,5 22,1 22,1 22,1 Other inventories 2,5 2,4 2,1 2,5 3,3 2,6 2,8 2,8 2,8 2,6 2,5 2,5 2,5 Trade receivables 8,7 6,8 6,5 10,3 9,0 8,3 9,2 9,1 9,2 8,5 8,3 8,2 8,2 Other receivables 1,5 1,1 1,3 2,2 1,9 1,6 1,8 1,8 1,8 1,7 1,7 1,6 1,6 Total current assets 35,9 27,7 27,7 40,7 37,5 33,9 37,4 37,2 37,8 35,3 34,6 34,4 34,4 Non-interest bearing debt Trade payables 5,5 5,2 5,4 7,3 6,7 6,0 6,7 6,7 6,7 6,2 6,0 6,0 6,0 Public duties payables 0,6 0,5 0,4 0,7 0,4 0,5 0,6 0,6 0,6 0,6 0,5 0,5 0,5 Taxes payable 3,4 2,4 0,6 2,2 2,1 2,1 2,3 2,3 2,3 2,1 2,1 2,1 2,1 Other current liabilities 2,8 2,1 1,5 2,1 2,6 2,2 2,5 2,5 2,5 2,3 2,2 2,2 2,2 Total non-interest bearing debt excl deferred tax 12,3 10,1 7,9 12,4 11,8 10,9 12,1 12,1 12,1 11,2 10,9 10,8 10,8 Deferred tax liabilities 10,8 7,9 8,0 10,3 9,7 9,3 - - - - - - - Total non-interest bearing debt incl deferred tax 23,0 18,0 15,9 22,6 21,5 20,2 12,1 12,1 12,1 11,2 10,9 10,8 10,8 Net working capital 23,6 17,6 19,8 28,3 25,7 23,0 25,3 25,2 25,7 24,1 23,7 23,6 23,6 Invested capital exlc goodwill and deferred tax 57,1 48,1 48,7 63,7 60,2 55,6 58,4 57,1 57,6 54,4 53,8 53,8 53,8 Invested capital inlc goodwill and deferred tax 62,3 54,0 53,7 67,3 63,7 60,2 71,0 68,8 68,7 65,0 63,9 63,5 63,5 Equity as % of invested capital 82,3 % 78,5 % 72,5 % 77,4 % 80,1 % 78,2 % 80,0 % 80,0 % 80,0 % 80,0 % 80,0 % 80,0 % 80,0 % NIBD as a % of Invested capital 17,7 % 21,5 % 27,5 % 22,6 % 19,9 % 21,8 % 20,0 % 20,0 % 20,0 % 20,0 % 20,0 % 20,0 % 20,0 % Invested capital (financing) 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 100 % 163

Appendix 5.9 Forecast Income Statement & balance sheet KG 2015E 2016E 2017E 2018E 2019E 2020E 2021E Operating revenue 13.271.700 14.129.671 15.043.348 14.648.908 14.803.107 15.224.173 15.604.777 Total revenue 13.377.874 14.242.708 15.163.695 14.766.099 14.921.531 15.345.966 15.729.615 Operating costs Cost of goods sold -8.493.888-8.986.471-9.537.483-9.258.110-9.325.957-9.545.556-9.784.195 Salaries and other personnel costs -1.353.713-1.441.226-1.534.422-1.494.189-1.509.917-1.552.866-1.591.687 Other operating costs -1.260.812-1.342.319-1.429.118-1.391.646-1.406.295-1.446.296-1.482.454 Total operating costs -11.108.413-11.770.016-12.501.022-12.143.944-12.242.169-12.544.718-12.858.336 EBITDA 2.269.461 2.472.692 2.662.673 2.622.154 2.679.362 2.801.248 2.871.279 Depreciation -384.614-399.728-425.576-414.418-418.780-430.692-441.459 EBIT 1.884.847 2.072.964 2.237.096 2.207.737 2.260.582 2.370.556 2.429.820 Tax -527.757-580.430-626.387-618.166-632.963-663.756-680.350 NOPAT 1.357.090 1.492.534 1.610.709 1.589.571 1.627.619 1.706.800 1.749.470 Non-operating items Financial expenses -113.457-124.845-130.815-134.050-135.101-138.923-143.019 Tax shield financial expenses 31.768 34.957 36.628 37.534 37.828 38.898 40.045 Net financial expenses -81.689-89.889-94.186-96.516-97.272-100.025-102.973 Net profit 1.275.401 1.402.645 1.516.523 1.493.054 1.530.347 1.606.776 1.646.497 2015E 2016E 2017E 2018E 2019E 2020E 2021E Non-current assets Deferred tax assets 26.543 28.259 30.087 29.298 29.606 30.448 31.210 Licenses and rights 2.161.685 2.185.572 2.303.116 2.383.576 2.538.001 2.698.208 2.765.663 Buildings, real estate, operating accessories 2.787.057 2.896.583 3.083.886 3.003.026 3.034.637 3.120.955 3.198.979 Shares in associates 504.325 536.927 571.647 556.658 562.518 578.519 592.982 Non-current receivables 21.235 22.607 24.069 23.438 23.685 24.359 24.968 Total non-current assets exl goodwill 5.500.845 5.669.949 6.012.805 5.995.997 6.188.448 6.452.489 6.613.801 Goodwill 2.082.706 2.082.706 2.082.706 2.082.706 2.082.706 2.082.706 2.134.774 Total non-current assets incl goodwill 7.583.551 7.752.655 8.095.511 8.078.703 8.271.154 8.535.195 8.748.575 Current assets Biological assets 3.915.152 4.168.253 4.513.004 4.453.268 4.544.554 4.719.494 4.837.481 Other inventories 464.510 494.538 526.517 512.712 518.109 532.846 546.167 Trade receivables 1.526.246 1.624.912 1.729.985 1.684.624 1.702.357 1.750.780 1.794.549 Other receivables 305.249 324.982 345.997 336.925 340.471 350.156 358.910 Total current assets 6.211.156 6.612.686 7.115.504 6.987.529 7.105.491 7.353.275 7.537.107 Non-interest bearing debt Trade payables 1.114.823 1.186.892 1.263.641 1.230.508 1.243.461 1.278.831 1.310.801 Public duties payables 99.538 105.973 112.825 109.867 111.023 114.181 117.036 Taxes payable 384.879 409.760 436.257 424.818 429.290 441.501 452.539 Other current liabilities 411.423 438.020 466.344 454.116 458.896 471.949 483.748 Total non-interest bearing debt excl deferred tax 2.010.663 2.140.645 2.279.067 2.219.309 2.242.671 2.306.462 2.364.124 Deferred tax liabilities - - - - - - - Total non-interest bearing debt incl deferred tax 2.010.663 2.140.645 2.279.067 2.219.309 2.242.671 2.306.462 2.364.124 Net working capital 4.200.493 4.472.041 4.836.436 4.768.219 4.862.821 5.046.813 5.172.984 Invested capital exlc goodwill and deferred tax 9.701.338 10.141.989 10.849.242 10.764.216 11.051.268 11.499.302 11.786.785 Invested capital inlc goodwill and deferred tax 11.784.044 12.224.695 12.931.948 12.846.922 13.133.974 13.582.008 13.921.559 NIBD 2.356.809 2.444.939 2.586.390 2.569.384 2.626.795 2.716.402 2.784.312 164

Appendix 5.10 Historical sales premium LSG and peers LSG: Sales premium LSG MHG: SALM: GSF: Lerøy Seafood Group 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating income 5 616 592 6 290 898 6 057 053 7 473 807 8 887 671 9 176 873 9 102 941 10 764 714 12 579 465 Avg salmon price 32,3 25,8 26,4 30,9 37,3 32,0 26,6 39,6 40,3 32,3 35,1 Avg achieved price 75,4 70,8 65,3 68,9 76,1 67,2 59,3 74,3 79,5 70,8 71,3 Sales premium 2,33 2,75 2,48 2,23 2,04 2,10 2,23 1,88 1,97 2,22 2,04 Sales premium industry Industry average 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating income 3 258 379 5 767 435 5 681 306 6 520 547 7 503 807 7 789 217 7 688 455 9 643 634 11 926 290 Average period Average period Average 5 years Average 5 years Avg salmon price 32,3 25,7 26,4 30,9 37,4 31,8 26,6 39,6 40,4 32,3 35,1 Avg achieved price 43,0 40,9 40,3 44,4 52,3 46,2 42,2 56,4 58,0 47,1 51,0 Sales premium 1,33 1,59 1,53 1,43 1,40 1,45 1,59 1,43 1,43 1,46 1,46 Source: Compiled by authors', annual reports LSG and peers 2005-2014 Marine Harvest Group Sales premium 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating income 5 640 500 14 091 500 13 486 900 14 619 500 15 281 200 16 132 800 15 420 400 19 177 300 25 300 400 Average period Average 5 years Avg salmon price 32,4 25,7 26,4 31,0 37,4 31,7 26,6 39,6 40,4 32,4 35,1 Avg achieved price 52,3 41,5 41,3 44,7 51,8 47,1 39,3 55,8 60,4 48,2 50,9 Sale premium 1,6 1,6 1,6 1,4 1,4 1,5 1,5 1,4 1,5 1,5 1,4 Salmar Sales premium 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating income 1 240 668 1 665 530 1 704 242 2 376 262 3 399 868 3 800 204 4 180 414 6 228 305 7 160 010 Average period Average 5 years Avg salmon price 32,4 25,7 26,4 31,0 37,4 31,7 26,6 39,6 40,4 32,4 35,1 Avg achieved price 28,2 26,0 26,2 30,9 43,0 36,5 40,7 54,2 50,8 37,4 45,1 Sale premium 0,9 1,0 1,0 1,0 1,1 1,2 1,5 1,4 1,3 1,1 1,3 Grieg Seafood Sales premium 2006 2007 2008 2009 2010 2011 2012 2013 2014 Operating income 535 756 1 021 810 1 477 029 1 612 619 2 446 490 2 046 991 2 050 065 2 404 215 2 665 284 Average period Average 5 years Avg salmon price 32,4 25,7 26,4 31,0 37,4 31,7 26,6 39,6 40,4 32,4 35,1 Avg achieved price 16,09 25,25 28,55 33,08 38,10 34,07 29,29 41,41 41,17 31,9 36,8 Sale premium 0,50 0,98 1,08 1,07 1,02 1,07 1,10 1,05 1,02 1,0 1,1 165

Cost of Capital Appendix 6.1- Historical capital structure LSG and peers Lerøy 31.12.05 31.12.06 31.12.07 31.12.08 31.12.09 31.12.10 31.12.11 31.12.12 31.12.13 31.12.14 17.04.2015 Shareprice 51 76 76 32 77 139 79 137 172 259,5 223,46 stock outstanding 36 909 41 077 48 177 53 577 53 577 54 577 54 577 54 577 54 577 54 577 368 54 577 368 MVE 1 872 246 3 139 803 3 682 505 1 702 248 4 099 337 7 613 164 4 320 861 7 469 845 9 399 797 14 165 119 12 195 859 NIBD 398 991 1 452 900 1 738 609 2 119 927 1 435 524 1 286 074 1 584 720 2 266 007 2 201 238 2 006 914 2 006 914 MVE/(MVE+NIBD) 0,82 0,68 0,68 0,45 0,74 0,86 0,73 0,77 0,81 0,88 0,86 10 year 5 year Average period 0,75 0,81 SalMar 31.12.05 31.12.06 31.12.07 31.12.08 31.12.09 31.12.10 31.12.11 31.12.12 31.12.13 31.12.14 17.04.2015 Shareprice 0 0 26,5 19,97 34,24 51,09 27,04 43,93 64,85 109,94 108,56 stock outstanding 102 028 102 923 102 714 103 000 103 000 111 583 113 300 113 300 113 300 MVE - - 2 703 750 2 055 366 3 516 914 5 262 270 2 785 120 4 901 854 7 347 505 12 456 202 12 299 848 NIBD 476 532 767 562 806 980 987 015 783 647 1 809 929 2 654 557 2 746 656 1 771 239 2 299 155 2 299 155 MVE/(MVE+NIBD) - - 0,77 0,68 0,82 0,74 0,51 0,64 0,81 0,84 0,84 10 year 5 year Average period 0,74 0,71 Marine harvest 31.12.05 31.12.06 31.12.07 31.12.08 31.12.09 31.12.10 31.12.11 31.12.12 31.12.13 31.12.14 17.04.2015 Shareprice 22,48 62,58 26,51 14,05 49,93 61,56 30,51 52,42 69,22 100,27 94,85 stock outstanding 138 346 347 265 347 890 347 690 357 490 357 490 358 110 374 800 410 400 410 400 410 400 MVE 3 110 009 21 731 831 9 222 559 4 885 039 17 849 476 22 007 084 10 925 936 19 647 016 28 407 888 41 150 808 38 926 440 NIBD 1 650 198 6 991 000 6 591 600 7 778 500 5 056 000 5 665 000 6 474 600 4 787 200 7 766 200 11 417 200 11 417 200 MVE/(MVE+NIBD) 0,65 0,76 0,58 0,39 0,78 0,80 0,63 0,80 0,79 0,78 0,77 10 year 5 year Average period 0,70 0,76 Grieg 31.12.05 31.12.06 31.12.07 31.12.08 31.12.09 31.12.10 31.12.11 31.12.12 31.12.13 31.12.14 17.04.2015 Shareprice 0 0 0 2,78 9,15 19,3 5,53 12,28 24,56 27,51 26,43 stock outstanding 0 0 0 76512 111 662 111 662 111 662 111 662 111 662 111 662 111 662 MVE - - - 212 703 1 021 707 2 155 077 617 491 1 371 209 2 742 419 3 071 822 2 951 227 NIBD 464 451 668 653 1 157 378 1 505 599 1 369 774 1 074 304 1 463 635 1 554 400 1 470 495 1 617 667 1 617 667 MVE/(MVE+NIBD) - - - 0,12 0,43 0,67 0,30 0,47 0,65 0,66 0,65 10 year 5 year Average period 0,49 0,55 31.12.08 31.12.09 31.12.10 31.12.11 31.12.12 31.12.13 31.12.14 17.04.2015 Average industry 0,41 0,69 0,77 0,54 0,67 0,76 0,79 0,78 166

Appendix 6.2 Default-free bond yield 1998 2014 Source: Norges bank Year 10-year yield 5 year avg 10 year avg 15 year avg 2014 2,52 % 2,77 % 3,49 % 4,21 % 2013 2,58 % 2012 2,10 % 2011 3,12 % 2010 3,52 % 2009 4,00 % 2008 4,47 % 2007 4,78 % 2006 4,07 % 2005 3,74 % 2004 4,36 % 2003 5,04 % 2002 6,38 % 2001 6,24 % 2000 6,22 % 1999 5,52 % 1998 5,40 % 167

Appendix 6.3 - BETA calculations Source: Authors creation / Yahoo Finance / Oslobørs Weekly LSG: Regression Statistics Multiple R 0.29950432 Lerøy Seafood Weekly R Square 0.08970284 Adjusted R Square 0.08077835 Standard Error 0.03609759 Observations 104 ANOVA df SS MS F Significance F Regression 1 0.01309723 0.01309723 10.0513212 0.00201055 Residual 102 0.13290968 0.00130304 Total 103 0.14600692 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 0.00292256 0.00358748 0.81465629 0.41716707-0.0041932 0.01003831-0.0041932 0.01003831 OSEBX 0.56695114 0.1788274 3.17038187 0.00201055 0.21224785 0.92165444 0.21224785 0.92165444 Monthly LSG: Regression Statistics Multiple R 0,402121095 R Square 0,161701375 Adjusted R Square 0,147247951 Standard Error 0,086524084 Observations 60 ANOVA df SS MS F Significance F Regression 1 0,0837562 0,0837562 11,1877552 0,00144805 Residual 58 0,43421219 0,00748642 Total 59 0,5179684 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 0,009090251 0,01145511 0,79355447 0,43068946-0,0138396 0,03202014-0,0138396 0,03202014 OSEBX 0,837716267 0,25045256 3,34481018 0,00144805 0,336381 1,33905153 0,336381 1,33905153 Weekly MHG: Regression Statistics Multiple R 0.29595425 Marine Harvest Weekly R Square 0.08758892 Adjusted R Square 0.07864371 Standard Error 0.03186591 Observations 104 ANOVA df SS MS F Significance F Regression 1 0.00994286 0.00994286 9.79171523 0.00228601 Residual 102 0.10357452 0.00101544 Total 103 0.11351739 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 0.00380298 0.00316692 1.20084364 0.23259308-0.0024786 0.01008456-0.0024786 0.01008456 OSEBX 0.49398254 0.15786368 3.12917165 0.00228601 0.18086069 0.8071044 0.18086069 0.8071044 168

Monthly MHG Regression Statistics Multiple R 0,342912985 R Square 0,117589316 Adjusted R Square 0,102375338 Standard Error 0,096956271 Observations 60 ANOVA df SS MS F Significance F Regression 1 0,07265691 0,07265691 7,72903187 0,0073146 Residual 58 0,54523008 0,00940052 Total 59 0,61788698 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 0,007365537 0,01283625 0,57380777 0,56831644-0,018329 0,03306007-0,018329 0,03306007 OSEBX 0,780237674 0,28064956 2,78011364 0,0073146 0,21845654 1,34201881 0,21845654 1,34201881 Weekly SalMar: Regression Statistics Multiple R 0.31801463 SalMar Weekly R Square 0.10113331 Adjusted R Square 0.09232089 Standard Error 0.03861051 Observations 104 ANOVA df SS MS F Significance F Regression 1 0.01710843 0.01710843 11.4762258 0.00100269 Residual 102 0.1520587 0.00149077 Total 103 0.16916713 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 0.00662436 0.00383722 1.72634242 0.0873135-0.0009868 0.01423546-0.0009868 0.01423546 OSEBX 0.64797898 0.1912764 3.38765786 0.00100269 0.26858316 1.02737481 0.26858316 1.02737481 Monthly SalMar Regression Statistics Multiple R 0,483187488 R Square 0,233470148 Adjusted R Square 0,220254116 Standard Error 0,078192762 Observations 60 ANOVA df SS MS F Significance F Regression 1 0,10800986 0,10800986 17,6656768 9,212E-05 Residual 58 0,35461827 0,00611411 Total 59 0,46262813 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 0,009602083 0,0103521 0,92754891 0,35748556-0,0111199 0,03032407-0,0111199 0,03032407 OSEBX 0,951305829 0,22633672 4,20305565 9,212E-05 0,49824366 1,404368 0,49824366 1,404368 169

Weekly Grieg Seafood Regression Statistics Multiple R 0.31843257 Grieg Seafood Weekly R Square 0.1013993 Adjusted R Square 0.09258949 Standard Error 0.04416598 Observations 104 ANOVA df SS MS F Significance F Regression 1 0.02245144 0.02245144 11.5098164 0.00098655 Residual 102 0.19896467 0.00195063 Total 103 0.22141611 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 0.00477406 0.00438934 1.08764924 0.27931339-0.0039322 0.01348029-0.0039322 0.01348029 OSEBX 0.74229738 0.21879819 3.39261203 0.00098655 0.3083122 1.17628256 0.3083122 1.17628256 Monthly Grieg Seafood Regression Statistics Multiple R 0,298920678 R Square 0,089353572 Adjusted R Square 0,073652771 Standard Error 0,117944402 Observations 60 ANOVA df SS MS F Significance F Regression 1 0,07916711 0,07916711 5,69102013 0,02033853 Residual 58 0,80683116 0,01391088 Total 59 0,88599827 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95,0% Upper 95,0% Intercept 0,008019484 0,01561491 0,51357868 0,6094976-0,0232372 0,03927612-0,0232372 0,03927612 OSEBX 0,814443302 0,34140179 2,38558591 0,02033853 0,13105337 1,49783324 0,13105337 1,49783324 170

Appendix 6.4 Operating- and financial Risk External risks Strategic risks Operational risks Type of risk Commodity prices GDP Growth Political stability Commercial law Intensity of rivalry Competitive advantage Supplier power Customer power Market growth substitute products Lifecycle Cost structure Success in R&D Product quality/innovation Brand name awareness Efficiency Quality of management/staff Quality of control systems Low, moderate or high risk Moderate Moderate low Moderate Moderate Moderate/High low low Moderate/high Low Moderate Low/moderate Low Low/moderate Low Low Low/moderate Assessment of LSG's ability to manage operating risk Good/moderate Have vast amount of licenses, stable growth in GDP and demand, stable prices on supply and demand side Good/moderate New strategic investments in VAP, one of the big players, demand is increasing, expensive relative to other sources of protein, fish feed producers can transfer cost to the industry Good/moderate Mature firm with experience in the market, higher costs than competitors, but also higher revenue pr KG in industry - successful R&D and innovation, known to customers, low/medium efficiency in production, experienced management/staff, new investments to increase efficiency and reduce costs Type of risk Low, moderate or high risk Assessment of LSG's ability to manage operating risk Financial leverage Low Good - lowest financial leverage in the industry Loan characteristics Interest rate - floating and swap Maturity - long term Currency - primarily NOK Moderate Low Low Good - Floating interest rates leaves them exposed to fluctuations (relatively stable in Norway), long maturities, almost all debt in home currency. Appendix 6.5 Credit Rating Source: Authors creation / Petersen & Plenborg (2012) - Financial Statement Analysis pg. 271-298 LSG three year median AAA AA A BBB BB B CCC EBIT Interest cover 20,4 x EBITDA interest cover 24,4 x Free operating cash flow/total debt 45,08 % x FFO/total debt 43,73 % x ROC 14,60 % x Operating income/revenue 17,61 % x Long-term debt/capital 22,60 % x Total debt/capital 56,20 % x Rating A 171

Credit rating 2011-2014 AAA AA A BBB BB B CCC Frequency 0 4 1 2 1 0 0 Weight 7 6 5 4 3 2 1 Frequency * Weight 0 24 5 8 3 0 0 Sum 40 Sum frequency 8 Average 5 LSG credit rating A LSG Aaa Aa A Baa Ba B Caa-c EBITA/Average assets 14.20 % x Operating margin 17.90 % x EBITA margin 14.72 % x EBITA/IntExp 20.4 x (FFO+IntExp)/IntExp 17 x Debt/EBITDA 1.5 x Debt/BookCap 41.80 % x FFO/Debt 43.70 % x Retained cash flow/netdebt 24.30 % x CAPEX/DepExp 1.12 x revenue volatility 10.10 x Rating Baa Appendix 6.6 Cost of debt 2010 2011 2012 2013 2014 avg 5 year Risk-free 2,58 % 2,10 % 3,12 % 3,52 % 4,00 % 3,06 % LSG 5,70 % 4,60 % 4,90 % 5,70 % 4,90 % 5,16 % Spread 3,12 % 2,50 % 1,78 % 2,18 % 0,90 % 2,10 % SAL 5,60 % -9,50 % 4,60 % 5,20 % 3,10 % 1,80 % Spread 3,02 % -11,60 % 1,48 % 1,68 % -0,90 % -1,26 % GSF 3,60 % 4,80 % 7,20 % 2,40 % -0,20 % 3,56 % Spread 1,02 % 2,70 % 4,08 % -1,12 % -4,20 % 0,50 % MHG 18,3 % 14,2 % 12,5 % 1,0 % 10,7 % 11,34 % Spread 15,72 % 12,10 % 9,38 % -2,52 % 6,70 % 8,28 % 172

Valuation Appendix 7.1 FCFF Cash flow 2010 2011 2012 2013 2014 2015E 2016E 2017E 2018E 2019E 2020E 2021E NOPAT 872.491 370.313 1.386.813 1.450.578 1.357.090 1.492.534 1.610.709 1.589.571 1.627.619 1.706.800 1.749.470 Change in deferred tax liabilities -176.335 146.765 256.514 44.290-1.531.262 - - - - - - Depreciation 271.899 291.768 307.175 369.480 384.614 399.728 425.576 414.418 418.780 430.692 441.459 Change in NWC 348.837-625.866-1.067.334 34.781-135.319-271.548-364.396 68.217-94.601-183.993-126.170 CAPEX -546.539-660.144-1.016.577-784.876-415.567-568.832-768.433-397.609-611.231-694.734-654.839 FCFF 770.353-477.164-133.409 1.114.253-340.444 1.051.882 903.457 1.674.596 1.340.567 1.258.766 1.409.920 Changes in NIBD 298.646 681.293-64.775-194.324 349.895 88.130 141.451-17.005 57.410 89.607 67.910 Net financial expenses after tax -48.822-57.959-69.373-77.452-81.689-89.889-94.186-96.516-97.272-100.025-102.973 FCFE 1.020.177 146.169-267.557 842.477-72.238 1.050.124 950.721 1.561.075 1.300.705 1.248.348 1.374.857 Dividend -1.020.177-146.169 267.557-842.477 72.238-1.050.124-950.721-1.561.075-1.300.705-1.248.348-1.374.857 Cash surplus - - - - - - - - - - - Appendix 7.2 Multiples 2015E LSG Nordea Pareto Fonds fin Average P/E 13,8 10,7 12,4 12,30 EV/Sales 1,1 1,3 1,3 1,23 EV/EBIT 9,4 10,4 9,9 9,90 EV/EBITDA 7,5 7,3 7,9 7,57 P/BV 1,9 1,81 1,5 1,74 2015E MHG Nordea Pareto Fonds fin Average P/E 16,4 13,7 12,6 14,23 EV/Sales 1,8 1,8 1,8 1,80 EV/EBIT 12,1 13 11,2 12,10 EV/EBITDA 9,6 9,6 8,9 9,37 P/BV 2,5 2,3 2,3 2,37 2015E SALM Nordea Pareto Fonds fin Average P/E 11,9 10 11,2 11,03 EV/Sales 2,4 2,2 2,4 2,33 EV/EBIT 9,5 8,4 9,8 9,23 EV/EBITDA 8,3 7,3 8,2 7,93 P/BV 2,6 2 2,5 2,37 173

2015E Grieg Nordea Pareto Fonds fin Average P/E 11 11,8 7,3 10,03 EV/Sales 1,6 0,9 1,3 1,27 EV/EBIT 10 13,6 7,1 10,23 EV/EBITDA 7,8 7,7 5,6 7,03 P/BV 1,1 1,3 1 1,13 2014 Lerøy MHG SALM GSF Harmonic mean Share price EV/Sales 1,12 1,96 2,15 1,68 1,91 388,6 EV/EBIT 7,87 11,53 7,92 13,45 10,44 308,4 EV/EBITDA 6,54 9,44 6,95 9,54 8,46 297,4 EV/Kilo 89,35 120,2 111,1 71,4 95,77 226,0 2015E Lerøy MHG SALM GSF Harmonic mean Share price EV/Sales 1,06 1,80 2,40 1,27 1,70 362,8 EV/EBIT 7,16 12,1 9,23 10,23 10,39 307,1 EV/EBITDA 6,00 9,37 7,93 7,03 8,00 310,6 EV/Kilo 83,35 112,22 112,72 64,19 89,92 221,8 (1000 NOK), 17.04.2015 Shares NIBD Share price Market cap Enterprise Value MHG 410 377,76 11 417 200 94,85 38 924 330 50 341 530 GSF 111 662,00 1 617 667 26,90 3 003 708 4 621 375 SALM 113 300,00 2 299 155 118,00 13 369 400 15 668 555 Multiple valuation EV/sales EV/EBITDA EV/EBIT P/B EV/KG 2014 2015E 2014 2015E 2014 2015E 2014 2015E 2014 2015E MHG 2,0 1,8 9,4 9,4 11,5 12,1 2,6 2,4 120,2 112,2 GSF 1,7 1,3 9,5 7,0 13,4 10,2 1,4 1,1 71,4 64,2 SALM 2,2 2,4 7,0 7,9 7,9 9,2 2,6 2,4 111,1 112,7 Harmonic mean 1,9 1,7 8,5 8,0 10,4 10,4 2,0 1,7 95,8 89,9 LSG (1000 NOK) Sales 12 579 465 13 271 700 EBITDA 2 252 076 2 269 461 EBIT 1 882 596 1 884 847 Book value E 8 079 596 9 427 235 Harvest volume 158 300 166 000 Enterprise value 24 031 691 22 627 052 19 056 202 18 152 082 19 657 354,89 19 583 592,32-15 159 208 14 926 966 NIBD + minority interests 2 824 196 2 824 196 2 824 196 2 824 196 2 824 196 2 824 196-2 824 196 2 824 196 Estimated value of equity 21 207 495 19 802 856 16 232 006 15 327 886 16 833 158,89 16 759 396,32 16 136 545 16 358 798 12 335 012 12 102 770 shares 54 577,37 54 577,37 54 577,37 54 577,37 54 577,37 54 577,37 54 577,37 54 577,37 54 577,37 54 577,37 Estimated share price 388,6 362,8 297,4 280,8 308,4 307,1 295,7 299,7 226,0 221,8 Share price 17.08.2015 235 235 235 235 235 235 235 235 235 235 Upside potential 65 % 54 % 27 % 20 % 31 % 31 % 26 % 28 % -4 % -6 % High 444 532 342 338 412 366 392 409 297 291 Low 335 257 235 241 222 267 200 195 155 143 Source: Authors' creation, bloomberg 174

Appendix 7.3 Scenario 3, Changes in fundamental input factors Best-case scenario 2015E 2016E 2017E 2018E 2019E 2020E 2021E Harvest volumes 169.000 181.000 193.000 205.000 217.000 229.000 240.000 Premium 1,85 1,85 1,85 1,95 2,00 2,00 2,00 Spot 43,00 43,00 43,00 41,00 39,50 39,00 38,00 Operating revenue 13.443.950 14.398.550 15.353.150 16.389.750 17.143.000 17.862.000 18.240.000 COGS per KG -49,3-49,3-48,5-48,8-47,4-46,8-45,6 Total operating costs per KG -65,0-65,0-64,2-64,5-63,0-62,2-60,6 EBIT/KG 12,9 12,9 13,7 13,8 14,4 14,3 13,9 NOPAT 1.568.296 1.686.807 1.909.183 2.038.085 2.255.182 2.349.768 2.399.494 FCFF -227.093 1.192.605 1.177.337 1.303.173 1.618.394 1.722.478 2.061.449 Estimated enterprise value 28744474 Estimated price per share 486 Upside compared to base case 56 % Source: Author's creation Worst-case scenario 2015E 2016E 2017E 2018E 2019E 2020E 2021E Harvest volumes 163.000 170.000 176.000 185.000 195.000 203.000 208.000 Premium 2,00 2,00 2,05 2,10 2,10 2,10 2,10 Spot 39 35 33 32 32 32 32 Operating revenue 12.714.000 11.900.000 11.906.400 12.432.000 13.104.000 13.641.600 13.977.600 COGS -50,7-46,2-44,6-44,4-45,0-45,0-45,0 Total operating costs -66,1-60,0-58,0-57,6-58,3-58,3-58,3 EBIT/KG 10,3 8,6 8,3 8,2 7,6 7,6 7,6 NOPAT 1.208.522 1.051.379 1.051.945 1.098.382 1.063.405 1.107.032 1.134.299 FCFF -172.183 1.549.426 871.265 669.600 485.217 596.727 820.535 Estimated enterprise value 12.554.240 Estimated price per share 182 Upside compared to base case -42 % Source: Authors creation 175