New frontiers in Systematic Commodities

Transcription

1 New frontiers in Systematic Commodities J Scott Kerson Head of Commodities, AHL / Man Systematic Strategies For institutional/professional investor use only. Not for public distribution Wien, 24. April 2013 Ihr Firmenlogo

2 Important notes This material is communicated by Man Investments AG ( the Company ), which is authorised and regulated by the Swiss Financial Market Supervisory Authority FINMA. This material is only to be communicated to investment professionals and professional clients only and should not be relied upon by any other person. This material is proprietary information of the Company and its affiliates and may not be reproduced or otherwise disseminated in whole or in part without prior written consent from the Company. The Company believes its data and text services to be reliable, but accuracy is not warranted or guaranteed. We do not assume any liability in the case of incorrectly reported or incomplete information. Information contained herein is provided from the Man database except where otherwise stated. Please be aware that investment products involve investment risks, including the possible loss of the principal amount invested. Alternative investments can involve significant risks and the value of an investment may go down as well as up. Returns may increase or decrease as a result of currency fluctuations. The data used herein constitutes the latest data available at the time of production. This material is not suitable for US persons. Man

3 Introduction Diagnosing the patient Searching for cures Challenges and solutions

4 The evolution of modern commodity markets Securities exchange formally established in Amsterdam James Man founds a sugar cooperage in London Commodity exchanges formally organised Chicago Mercantile Exchange formed from the Chicago Butter & Egg Board OTC market making in uranium, wood pulp, electricity, coal, iron ore, steel, rhodium, house prices Modern commodity futures contracts, by first year of trading: Sugar Live cattle Cocoa, copper, Silver corn, cotton, oats, soybean meal, soybean oil, soybeans, wheat Orange juice Lumber Lean hogs Platinum Coffee Feeder cattle Man 2013 Source: Man database and Vanguard, Investment Case for Commodities, Gold Palladium, zinc Nickel Heating Unleaded gasoline Crude oil Aluminium, propane Rough rice Natural gas Coal German Power Iron Ore? 4

5 Introduction Diagnosing the patient Searching for a cure Challenges and solutions

6 Active commodity trading strategies The patient is not well Poor performance goes viral in the post-crisis world Sales and Marketing HFRX Macro Commodity Traders Legal and Compliance Back office HFRX index of macro commodity traders peaks 31 December 2008, currently ~14% below peak Newedge Trend Index of CTAs peaks 29 April 2011, currently ~9% below peak Newedge Trend Followers 132 investment professionals 2 Research 94 Trading 15 Operations and client 23 Man To a certain extent, the start and end dates of crisis events are subjective and different sources may suggest different date ranges, leading to different performance figures. As a consequence, they give no indication of likely performance. Source: Man database and Bloomberg.

7 Exposure to structural breaks Some common faults in systematic investing Inability to navigate structural breaks in market structure Lack of dynamic research and development Example: Specification change to Heating Oil futures distorts algorithmic Carry and Curve based strategies Man There is no guarantee of trading performance and past performance is no indication of current or future performance/results. Source: Man database and Bloomberg.

8 Introduction Diagnosing the patient Searching for a cure Challenges and solutions

9 Modelling price dynamics Market specific factors vs macro factors It s hard to build multivariate models when they are dominated by a single risk factor Trader and model strategy diversification and skill degraded, because Legal and Compliance Index commodities vs stocks Back office Post-crisis period characterised by high cross-asset correlations Risk-on/risk-off an inherently difficult factor to model Search for new markets and models Alternative commodities vs stocks 132 investment professionals 2 Research 94 Trading 15 Operations and client 23 Man Alternative Commodities represent weighted average return of front month API 2 Coal, Phelix Annual Baseload Power, Asia Clear Iron Ore, and Nordpool Yearl Baseload Power. Correlation is expanding window. All data is monthly since 30 April Commodity index represented by: Dow Jones-UBS Commodity Total Return Index. Stocks represented by: FTSE World Index. Source: Man database and Bloomberg.

10 New markets, new opportunities Where micro dominates macro Terminal markets for some non-traditional commodities can be as large or larger than established markets USD bn annual production Sales and Marketing Legal and Compliance Back office Commodity USD bn ann. prod. Used for Oil 3190 Transport, power gen, pet chem Natural Gas 1120 Power gen, manufacturing Coal 998 Power gen, blast furnace Iron Ore 420 Steel making Course Grains 325 Food, biofuel Gold 198 Investment, jewelry Copper 122 Construction, manufacturing 132 investment professionals 2 Research 94 Trading 15 Operations and client 23 Man As at 31 December Sources: International Energy Agency, US Federal Energy Regulatory Commission, World Coal Association, US Geological Survey, US Department of Agriculture, World Gold Council, International Copper Study Group. Source: Man database.

11 German electricity A strong trend based on an uncorrelated risk Increasingly synchronous moves in stocks, oil, metals, Euro, but German electricity prices driven by local supply and demand patterns DAX Index (LHS) Imperative for a balanced market ensures market clears at a fundamentally correct price Phelix Base Load Annual (x2, RHS) Brent Crude (RHS) Man Date range: 1 January 2011 to 31 March Adjusted price simulates the cost of buying one unit of a market adjusting the history for the rolling of contracts. There is no guarantee of trading performance and past or projected performance is not a reliable indicator of future performance. Returns may increase or decrease as a result of currency fluctuations. The above example is intended as illustration of a typical investment consideration and/or strategy implementation. Any organization, financial instrument or security described herein are mentioned for reference purposes only and therefore, should not be construed as commentary on the merits thereof or a recommendation for purchase or sale. Views expressed herein are subject to change at any time without notice. Source: Bloomberg.

12 Application: Trend following strategies on new markets Trends can persist when micro influences drive prices 1 January 2004 to 17 April 2013 (base year = 100) Simulated strategy performance (illustration only) Trend Following Phelix Base Strategy Information Ratio Trend Following WTI Crude Oil 1.1 Trend Following Phelix Base Annual 0.2 Correlation of strategy returns: 11% Trend Following WTI Crude Oil Man Any financial instruments mentioned in this material are for reference purposes only. This material should not be construed as a commentary on the merits thereof or a recommendation for purchase or sale. Please note the above simulated data has been calculated by Man and is based on a wide range of assumptions and must therefore be used only for illustrative purposes. There is no guarantee of trading performance and past or projected performance is not a reliable indicator of future performance. Returns may increase or decrease as a result of currency fluctuations. Source: Bloomberg.

13 Application: New models of price dynamics Even when prices don t trend, key factors can 23 February 1998 to 31 December 2012 Simulated strategy performance (illustration only) Combination¹ Fundamental strategy Momentum strategy Carry strategy Strategy Information ratio Fundamental strategy 1.6 Momentum strategy 1.1 Carry strategy 1.2 Combination 1.7 Correlation properties Fundamental Momentum Carry Fundamental 1.00 Momentum Carry Man Please note the above simulated data has been calculated by Man and is based on a wide range of assumptions and must therefore be used only for illustrative purposes. The results of the "combination" is based on the specific allocations stated in footnote 1. Results may vary if the allocations are changed. There is no guarantee that the results can be replicated in actual portfolios. In addition, depending on the allocation percentages between the strategies and exposure to the combination portfolio, the end results may not necessarily result in an improvement in all situations. 1. Equally weighted combination. There is no guarantee of trading performance and past or projected performance is not a reliable indicator of future performance. Returns may increase or decrease as a result of currency fluctuations. Source: Man database.

14 Introduction Diagnosing the patient Search for a cure Challenges and solutions

15 The search for solutions Traditional active commodities strategies have performed poorly in recent years New markets Wide range of available uncorrelated OTC commodity markets, eg, Power, Bulks but liquidity and transparency must be carefully monitored New models Core strategies like Carry and Momentum can be bolstered by innovative research into uncorrelated strategies, eg, Fundamental, Behavioural Man

16 Putting it all into practice New markets and strategies require new portfolio management skills Implementation OTC contracts require specific execution skills Operations Clearing, allocation, and cash/margin management are more complex Credit risk OTC portfolios create counterparty exposure which must be carefully monitored and managed Man