Commodity Risk Management

Transcription

1 Commodity Risk Management KYOS Corporate Commodity Advisory Richard Cornielje

2 Agenda Introduction KYOS CCA Part I 1. How to determine your specific Commodity Risks 2. Understand the basics 3. What affects your costs and by which percentage 4. Risk management 5. Forward curves & price dynamics 6. Volatility of FX and Interest Rates Part II 7. Volatility of Commodities 8. Correlation & co-integration 9. Value-at-Risk (VAR) 10. Credit Risk (Potential Future Exposure) 11. Documentation (ISDA) 12. Accounting IFSR - IAS39 Commodity Formula Assistant Portfolio & Risk Management Tool 2

3 Introduction KYOS CCA Background Active since 1997 as Maycroft, since 2008 transformed into KYOS Strong focus on energy & commodity markets: trading, valuation, risk management Core competence: combine quantitative background with practical solutions Experienced and dedicated expert team Activities Modelling Apply quantitative financial techniques to Commodity markets Consulting Advise on commodity trading, valuation and risk management Training ( procurement & treasury ) Combine theory with real life examples 3

4 Introduction KYOS work & customers Recent Projects Customers Power plant valuation Gas storage and swing pricing Value long term tolling agreements Commodity price modelling based on fundamental co-integration Asphalt/Bitumen price formulas Energy % in Cement Bricks Glass Development VAR and capital allocation framework Credit Risk Exposure ( PFE s) Metal hedging advice in terms of Cash flow-at-risk (CfAR) Our advice is a result of thorough understanding of your business. 4

5 Hedging is an end stage.what is your risk? Construction Cement, Asphalt/Bitumen, Steel, Glass, Diesel.. aluminium Cable/wire Copper, Lead & Plastics olefins Beverage Steel / Aluminium cans packaging Transport Diesel/JetFuel / GasOil trains Chemicals Electricity, Steam, Naphta, Benzene, Xylene aromatics Energy Coal, Coke, Natural Gas, Oil, carbon electricity. Steel, Food, Glass, Cement, Brick, Sugar, Automotive, Retail, Pharmaceutical Your sector is exposed to commodities, energy is often one of them Commodity exposures can be quantified either direct or indirect..

6 ..treasurer & risk manager.what is your task? Treasury involvement Combine FX and Interest Rate exposures with Commodity exposures Discover differences in volatility & liquidity compared to FX & IR Discover the overlap of financial hedging opportunities of commodity risks Analyze sensitivity of hidden currency components Quantify value-at-risk ( or : cashflow-at-risk ) Determine an optimal risk profile in line with FX and IR Use your wallet to invite the proper banks to compare physical suppliers Introduce quantified Credit Risk (Potential Future Exposure) Think global but act local. KYOS CCA can quantify direct or in-direct Commodity Exposures

7 back to the basics and develop insight Barrel crude Abbr. bbl

8 a construction company consumes bitumen. Understanding the production process will certainly lead to a better understanding of the costs of : NYNAS Petroplus Total Shell ExxonMobil Question: Are you able to calculate the effect on your P&L of fast moving commodity prices..

9 ..we all consume OLEFINS and AROMATICS. Committee of chief risk officers (US): 9

10 know where your product fits in the circle.. Gather the correct information... 10

11 understanding the cost structure of suppliers 11 Analyze your suppliers: Balance sheet P&L statement EBITDA Cost structure Profit & margin breakdown Breakdown of Commodity costs Cement Materials Clay... Breakdown of Energy costs Coal Natural gas...

12 leads to improved predictability of your costs Float Glass Production Costs 12% 10% 20% Raw Materials Energy 9% Prime Labour 9% 12% 28% Overhead Depreciation Transport Other How about the predictability of your costs? Metals Glass Transport Plastics Cement/Bricks... 12

13 .from basics towards Risk Management Exposure Price Change Cashflow-at-Risk Treasurer questions: Funding horizon? Hedging horizon? Fix Floating mixture? 13

14 how to organise Risk Management.. Risk??? Market Credit Operational 14 Other Price Volume Liquidity Default Degradation Concentration Technical Administrative Models Legal Accounting & Tax Regulatory Fraud

15 counterparty risks Credit Exposure: Measure for the loss of market / replacement value in case of default Credit Exposure Current Exposure Potential Future Exposure Loss, if default occurs now. Worst case loss, if default occurs at a future point in time. Is the supplier with the best price also the best choice? Treasurer question : how do you rate your counterparties? Treasurer task- Search in Reuters for CDS market Rexam versus CrownCork 15

16 combine physical & financial markets Physical Exposure: Secured physical requirements Volumetric constraints Liquidity issues Market Price Exposure: Cashflow-at-risk: what is the risk? Floating or FIX Benchmark (EURIBOR?) Currency ( USD or EUR) Price Volume Liquidity Floating - price could rise - how much? Fix - price could fall - how much? Benchmark Currency Treasurer question: Normal EURUSD move in a single day ( in $ pips ) 16

17 .different curves & price dynamics than FX. Commodity curves examples Power Base Peak NatGas Base EUR/MWh EUR/Mwh nov nov dec dec jan jan feb Mar Q apr Q Q Q Q Q Q Sum Q Win Q Sum Q Win Cal Cal Cal Cal Cal Cal Cal Cal Contango Backwardation Seasonality spot vs 5 yr Aluminium 1800 Copper 6200 ( both quoted in $/MT ) 17

18 what is the volatility. know the basic rules Correct estimation is complicated because: Volatility is not directly observable We need to forecast future volatility levels, but can only measure in the past Volatility is generally heteroskedastic i.e. changes over time Volatility of commodities can bear seasonality Depends on time to maturity But we need volatility to: Estimate the short term risk of positions (VAR) Estimate the long term risk of positions (CFAR, PFE*) and assets Value options and flexible assets * PFE = Potential Future (Credit) Exposure A B A C U S Advisory 18

19 how to calculate volatility. Volatility = Annualized standard deviation of returns Calculation Steps 1. Take time series of prices during a sample period: price sample = {p 0,, p N } Calculate returns: 0 Mar-99 Jul-99 Nov-99 Mar-00 Jul-00 Nov-00 Mar-01 Jul-01 Nov-01 Mar-02 Jul-02 Nov-02 Mar-03 Jul-03 Nov-03 Mar-04 10% 8% p t p t 1 r = ln(p t) ln(p t p t 1 t ) 6% 4% 2% 0% Mar-99 Jul-99 Nov-99 Mar-00 Jul-00 Nov-00 Mar-01 Jul-01 Nov-01 Mar-02 Jul-02 Nov-02 Daily return Mar-03 Jul-03 Nov-03 Mar-04-2% -4% -6% -8% A B A C U S Advisory 19

20 .what is the probability of the returns. Calculation Steps Continued 3. Estimate standard deviation of returns σ est = 1 N N 1 t= 1 (r t r) 2 Time series of returns Probability density of returns 10% 8% 6% Daily return 4% 2% 0% -2% -4% Mar-99 Jul-99 Nov-99 Mar-00 Jul-00 Nov-00 Mar-01 Jul-01 Nov-01 Mar-02 Jul-02 Nov-02 Mar-03 Jul-03 Nov-03 Mar-04 Standard Deviation -6% -8% 20

21 and use Volatility for next year s budget Calculation Steps Continued 4. Calculate annualization factor Annualizat ionfactor = number of(trade) days peryear number of(trade) days used to calculate areturn 5. Rescale standard deviation to 1-year holding period volatility = standard deviation of returns * annualization factor 2 Mean ± 1 Standard Deviation Square Root of Time Rule 1,5 1 0,5 68% probability time in months 21

22 Treasurer: are you familiar with your volatility. Treasurers question Volatility % 1 months EURUSD. 3 months EURIBOR. A B A C U S Advisory 22

23 ...theory starts to grow into a practical approach... 23

24 are you familiar with correlation? is your commodity related to another commodity? Correlation for different scatter plots Source: Wikipedia 24

25 can you quantify this movement. How to measure correlation? Normalize covariance: Divide by standard deviations ρ est r,r = est cov (r1,r ) σ * 1 2 est r σ 1 2 est r2 = N 1 N N [ (r1,t r)*(r 1 2,t r2) ] t= 1 N 2 1 (r1, t r) 1 * (r 2,t r2 ) N 1 N t= 1 t= 1 Correlation = 1: The returns of the prices for the two products have the same sign, but not necessarily the same size. Correlation = -1: The returns of the prices for the two products have opposite signs, but not necessarily the same size. Correlation = 0: Return pairs can be any combination A B A C U S Advisory

26 better ways to quantify this price behaviour Co-integration Correlation: Commonality of two series of (daily) price changes Cointegration: Commonality of two series of (log) price levels Cointegration can be seen as mean reversion of price spreads, where the underlying prices contribute to the predictable adjustment to a different degree. Examples: National Income and National Savings Power price and Fuel prices Zeebrugge and TTF gas prices The concept was developed by Clive Granger and Robert Engle (Nobel prize 2003) A B A C U S Advisory 26

27 for the upcoming winter evenings. How to model co-integration Equilibrium relationship: In case of equilibrium: Y = a + b * t + c * X Deviation from equ.: Z = Y - a - b * t - c * X Z = 0 Y c * X = a + b * t SDE for 1 st commodity: dx = (µ X + η X * Z) * dt + σ X * dw X SDE for 2 nd commodity: dy = (µ Y - η Y * Z) * dt + σ Y * dw Y 27

28 use your old (..or recent..) school books. Appendix: Normal Distribution Table Probability content from - to z standard deviations Common percentiles for measuring risk 28

29 normal distribution of Commodity costs. 68.2% = 1*standard deviation 95.4% = 2*standard deviation A B A C U S Advisory 29

30 ..use quantification as a risk measurement tool What is my VAR.what is my Value-at-Risk? VAR is the maximum lossof MtM value on my pension fund portfolio over a certain holding period with a certain confidence: Holding period 95% P(return -? %) = 95% Investment = VAR = -9,3% x = Maximum loss: 9.3% Confidence level 30

31 & CHANGE theory into your practical approach... Value-at-Risk for a 5 day Aluminium position Annualized Volatility 51% * Underlying Price * 1,800 $/MT * Confidence-Multipl. * * Holding Period * 5/250 for 95% confidence = 168 $/MT 31

32 ...express the guts feeling into quantified figures... Value of quantified Value-at-Risk figures A good risk methodology should answer the following questions: How much value can be lost in total (downside focus)? Quantified risk for strategy A compared to strategy B (or C)? How to alter your strategy given an agreed maximum loss? 32

33 ...use Monte Carlo simulation & Co-integration... Common VAR methods Delta-Normal: Approximate contract values as a linear function of underlying prices Assume correlated Brownian Motion for underlying prices Calculate maximum loss based on percentile on normal return distribution Historical Simulation: Take historical sample of n-day prices changes (e.g. during last 100 or last 1,000 trading days) Calculate returns of current position for historical n-day price changes Calculate maximum loss based on worst return for 99% confidence, 5 th worst return for 95% confidence Monte-Carlo Simulation: Like historical simulation, but price changes come from a price simulation model Rarely observed extreme price changes can be included. 33

34 ...and act as a professional risk manager... Confidence levels and holding periods The choice of the holding period and confidence level depend on the type of position, for which risk needs to be assessed. Typical VAR measures are: 10-day liquidation VAR with 99% confidence: Basel II standard for risk reporting of financial institutions. It is assumed that all positions can be liquidated in 1 month time. The market risk during this liquidation period is assumed to be equivalent to holding the full position for 2 weeks (= 10 trading days). 1-day overnight VAR with 95% confidence: Common standard for internal risk reporting on proprietary books. The risk measure is used to internally asses the risk of overnight positions. 34

35 .natural gas formula example. EURcnt/M3 = x * (LSFO) + y * (GasOil) + z LSFO and GasOil in EUR

36 .we are able to analyze formula contracts. different energy providers use different sources..

37 .also in the strangest formats...

38 and isolate the underlying quantified volumes. By understanding the formula behind the contract you are able to define your complete exposure to: - Commodities - FX components Formulas Energy Dredging Beverage Construction - PetCoke, Natural Gas, Steam.. - Maasvlakte II - Can (metal) & Glass (energy) - Steel, Cement, Bitumen, Glass. Treasurers: your private gas consumption is linked to GasOil.

39 ..compare history & forwards of the underlying.. Treasurers: now you are able to start risk analyses & in co-operation with procurement.. make better prepared decisions

40 what is the sensitivity to price changes. what if GasOil moves 100$ up.. Treasurer question : can you isolate the currency exposure..

41 as this might justifies a $ price risk. YES treasurer.you CAN.isolate the Currency Risk.. Treasurer: should procurement buy in USD or in EUR?

42 from the basics to cashflow-at-risk.

43 from data to management decisions..

44 prepared decisions decisions.. 14% Strategy A versus Benchmark 12% 10% 8% 6% 4% 2% 0% mln mln mln mln 0.3 mln 1.1 mln 2.0 mln

45 from rough data to refined risk management Calculate the expected monthly payments..and adjust or maintain your strategy..it is now a well defined & thorough calculated strategy

46 including Credit Risk per counterparty....calculate the potential future exposure (PFE) on counterparties

47 from the basics tot cashflow-at-risk.. Proper Monte Carlo simulations leads to valuable insight in risks

48 ..now we can implement a risk driven approach.. Business areas risk limit profile A = Treasury B = Procurement Packaging C = Procurement Energy FX Interest rate Power Gas CO2 Risk Manager has now created diversification for different business areas such as Treasury and Procurement over time. 48

49 ...reasons for not having a policy... information is spread throughout subsidiaries ( decentralized ) - start mapping difficulty of correctly quantifying the exposure - quantify natural hedges & pass on procedures (clauses) managers have different view on RM objectives - agree on earnings volatility and calculate backwards managers not accountable - budgets FX-, IR- & Commodity Risk Management regulated markets in the past ( gas, electricity ) - markets have changed rapidly impact on competitive position of the company - steep learning curve in the market 49

50 ...unknown product range or documentation... futures, swaps and options - in line with FX and IR swaps are most commonly used - in line with FX and IR mark-to-market - liquid benchmarks have same MtM reporting functionality documentation - most financial commodity swaps fit in the ISDA (annex) - carbon is a physical product ( adjusted documentation) - physical power transactions documented under EFET 50

51 ..commodity hedges and accounting... IFRS - IAS39 Cashflow hedging in compliance & in-line with company policy Use liquid references in your purchasing contracts Make sure the hedge is in line with the underlying risk KYOS CCA runs hedge effectiveness tests Align purchasing contracts with financial opportunities 51

52 ..timing is good... Commodity prices have fallen to lower levels so now it is time to : Learn the basics, educate yourselves Adjust and align treasury, procurement & sales Create a competitive advantage Lower your costs by combined efforts Balance the need for flexibility given an agreed horizon Install risk limits in line with companies risk appetite Distinguish the company from competitors Risk Managers have an import role to play in this journey to success 52

53 ..success stories in practise... KYOS CCA has visited many European Industrials who incorporated physical procurement & financial hedging successfully Role Procurement physical and volumetric details secure the required goods maintain flexibility (quality, form) timing of delivery embed liquid benchmarks Role Treasury financial details companies hedging policy documentation quantify company risk manage financial risks 53 KYOS CCA has experience with Clients in following industries: -Cement/Bricks -Steel -Construction -Energy (incl Waste) -Glass -Base Metals -Chemical -Beverage -Retailers -Food/sugar -Pharmaceutical -.

54 KYOS CCA contact details Richard Cornielje KYOS Corporate Commodity Advisory 54 Lange Herenstraat 38 zwart 2011 LJ Haarlem (Netherlands) +31 (0)