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Trading on mean-reversion in energy futures markets

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  • Lubnau, Thorben
  • Todorova, Neda

Abstract

We study whether simple technical trading strategies enjoying large popularity among practitioners can be employed profitably in the context of hedge portfolios for Crude Oil, Natural Gas, Gasoline and Heating Oil futures. The strategies tested are based on mean-reverting calendar spread portfolios established with dynamic hedge ratios. Entry and exit signals are generated by so-called Bollinger Bands. The trading system is applied to twenty-two years of historical data from 1992 to 2013 for various specifications, taking transaction costs into account. The significance of the results is evaluated with a bootstrap test in which randomly generated orders are compared to orders placed by the trading system. Whereas we find most combinations involving the front-month and second-month futures to be significantly profitable for all commodities tested, the best results for the risk-adjusted Sharpe Ratio are obtained for WTI Crude Oil and Natural Gas, with Sharpe Ratios in excess of 2 for most combinations and a rather smooth performance for all calendar spreads. Based on our results, there is a serious doubt whether energy futures markets can be considered weakly efficient in the short-term.

Suggested Citation

  • Lubnau, Thorben & Todorova, Neda, 2015. "Trading on mean-reversion in energy futures markets," Energy Economics, Elsevier, vol. 51(C), pages 312-319.
    • Handle: RePEc:eee:eneeco:v:51:y:2015:i:c:p:312-319
    DOI: 10.1016/j.eneco.2015.06.018
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    as
    1. Delphine Lautier & Alain Galli, 2004. "Simple and extended Kalman filters: an application to term structures of commodity prices," Applied Financial Economics, Taylor & Francis Journals, vol. 14(13), pages 963-973.
    2. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    3. Paul Berhanu Girma & Albert S. Paulson, 1998. "Seasonality in petroleum futures spreads," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 18(5), pages 581-598, August.
    4. Hendrik Bessembinder & Kalok Chan, 1998. "Market Efficiency and the Returns to Technical Analysis," Financial Management, Financial Management Association, vol. 27(2), Summer.
    5. Mark Cummins & Andrea Bucca, 2012. "Quantitative spread trading on crude oil and refined products markets," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1857-1875, December.
    6. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Market Efficiency of Oil Spot and Futures: A Stochastic Dominance Approach," CIRJE F-Series CIRJE-F-705, CIRJE, Faculty of Economics, University of Tokyo.
    7. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    8. Alvarez-Ramirez, Jose & Alvarez, Jesus & Solis, Ricardo, 2010. "Crude oil market efficiency and modeling: Insights from the multiscaling autocorrelation pattern," Energy Economics, Elsevier, vol. 32(5), pages 993-1000, September.
    9. Darren Butterworth & Phil Holmes, 2002. "Inter-market spread trading: evidence from UK index futures markets," Applied Financial Economics, Taylor & Francis Journals, vol. 12(11), pages 783-790.
    10. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2010. "Market efficiency of oil spot and futures: A mean-variance and stochastic dominance approach," Energy Economics, Elsevier, vol. 32(5), pages 979-986, September.
    11. Wang, Tao & Yang, Jian, 2010. "Nonlinearity and intraday efficiency tests on energy futures markets," Energy Economics, Elsevier, vol. 32(2), pages 496-503, March.
    12. Joseph Man-Joe Leung & Terence Tai-Leung Chong, 2003. "An empirical comparison of moving average envelopes and Bollinger Bands," Applied Economics Letters, Taylor & Francis Journals, vol. 10(6), pages 339-341.
    13. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    14. Shleifer, Andrei, 2000. "Inefficient Markets: An Introduction to Behavioral Finance," OUP Catalogue, Oxford University Press, number 9780198292272, Decembrie.
    15. Levich, Richard M. & Thomas, Lee III, 1993. "The significance of technical trading-rule profits in the foreign exchange market: a bootstrap approach," Journal of International Money and Finance, Elsevier, vol. 12(5), pages 451-474, October.
    16. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo, 2008. "Short-term predictability of crude oil markets: A detrended fluctuation analysis approach," Energy Economics, Elsevier, vol. 30(5), pages 2645-2656, September.
    17. Koch, Nicolas, 2014. "Tail events: A new approach to understanding extreme energy commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 195-205.
    18. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    19. Abdulnasser Hatemi-J & Eduardo Roca, 2014. "Estimating the optimal hedge ratio in the presence of potential unknown structural breaks," Applied Economics, Taylor & Francis Journals, vol. 46(8), pages 790-795, March.
    20. repec:dau:papers:123456789/11712 is not listed on IDEAS
    21. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    22. Peter R. Locke & P. C. Venkatesh, 1997. "Futures market transaction costs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(2), pages 229-245, April.
    23. Christian Dunis & Jason Laws & Ben Evans, 2008. "Trading futures spread portfolios: applications of higher order and recurrent networks," The European Journal of Finance, Taylor & Francis Journals, vol. 14(6), pages 503-521.
    24. Tabak, Benjamin M. & Cajueiro, Daniel O., 2007. "Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility," Energy Economics, Elsevier, vol. 29(1), pages 28-36, January.
    25. Ki-Yeol Kwon & Richard Kish, 2002. "Technical trading strategies and return predictability: NYSE," Applied Financial Economics, Taylor & Francis Journals, vol. 12(9), pages 639-653.
    26. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    27. Marshall, Ben R. & Cahan, Rochester H. & Cahan, Jared M., 2008. "Can commodity futures be profitably traded with quantitative market timing strategies?," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1810-1819, September.
    28. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, August.
    29. Sanders, Dwight R. & Boris, Keith & Manfredo, Mark, 2004. "Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports," Energy Economics, Elsevier, vol. 26(3), pages 425-445, May.
    30. Julien Chevallier, 2013. "Price relationships in crude oil futures: new evidence from CFTC disaggregated data," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 15(2), pages 133-170, April.
    31. repec:dau:papers:123456789/2437 is not listed on IDEAS
    32. Szakmary, Andrew C. & Shen, Qian & Sharma, Subhash C., 2010. "Trend-following trading strategies in commodity futures: A re-examination," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 409-426, February.
    33. Paul Berhanu Girma & Albert S. Paulson, 1999. "Risk arbitrage opportunities in petroleum futures spreads," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(8), pages 931-955, December.
    34. C. L. Dunis & Jason Laws & Ben Evans, 2006. "Trading futures spreads: an application of correlation and threshold filters," Applied Financial Economics, Taylor & Francis Journals, vol. 16(12), pages 903-914.
    35. Shambora, William E. & Rossiter, Rosemary, 2007. "Are there exploitable inefficiencies in the futures market for oil?," Energy Economics, Elsevier, vol. 29(1), pages 18-27, January.
    36. Delphine Lautier, 2004. "Simple and extended Kalman filters : an application to term structures of commodity prices," Post-Print halshs-00152998, HAL.
    37. Miffre, Joelle & Rallis, Georgios, 2007. "Momentum strategies in commodity futures markets," Journal of Banking & Finance, Elsevier, vol. 31(6), pages 1863-1886, June.
    38. W. Brian Barrett & Robert W. Kolb, 1995. "Analysis of spreads in agricultural futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(1), pages 69-86, February.
    39. Delphine Lautier & A. Galli, 2004. "Simple and extended Kalman filters : an application to term structures of commodity prices," Post-Print halshs-00136139, HAL.
    40. Delphine Lautier & Alain Galli, 2004. "Simple and extended Kalman filters : an application to term structure of commodity prices," Post-Print halshs-00153042, HAL.
    41. Qian Shen & Andrew C. Szakmary & Subhash C. Sharma, 2007. "An examination of momentum strategies in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(3), pages 227-256, March.
    42. Wang, Yudong & Liu, Li, 2010. "Is WTI crude oil market becoming weakly efficient over time?: New evidence from multiscale analysis based on detrended fluctuation analysis," Energy Economics, Elsevier, vol. 32(5), pages 987-992, September.
    43. Fuertes, Ana-Maria & Miffre, Joëlle & Rallis, Georgios, 2010. "Tactical allocation in commodity futures markets: Combining momentum and term structure signals," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2530-2548, October.
    44. Abdulnasser Hatemi-J & Eduardo Roca, 2006. "Calculating the optimal hedge ratio: constant, time varying and the Kalman Filter approach," Applied Economics Letters, Taylor & Francis Journals, vol. 13(5), pages 293-299.
    45. repec:dau:papers:123456789/876 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

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    2. Adamantios Ntakaris & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators," Papers 1907.09452, arXiv.org.
    3. Yuanrong Wang & Yinsen Miao & Alexander CY Wong & Nikita P Granger & Christian Michler, 2023. "Domain-adapted Learning and Interpretability: DRL for Gas Trading," Papers 2301.08359, arXiv.org, revised Sep 2023.
    4. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    5. Day, Min-Yuh & Ni, Yensen, 2023. "Do clean energy indices outperform using contrarian strategies based on contrarian trading rules?," Energy, Elsevier, vol. 272(C).
    6. Adam Zaremba, 2019. "The Cross Section of Country Equity Returns: A Review of Empirical Literature," JRFM, MDPI, vol. 12(4), pages 1-26, October.
    7. Alexopoulos, Thomas A., 2018. "To trust or not to trust? A comparative study of conventional and clean energy exchange-traded funds," Energy Economics, Elsevier, vol. 72(C), pages 97-107.
    8. Phan, Dinh Hoang Bach & Narayan, Paresh Kumar & Gong, Qiang, 2021. "Terrorist attacks and oil prices: Hypothesis and empirical evidence," International Review of Financial Analysis, Elsevier, vol. 74(C).
    9. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, November.
    10. Zaremba, Adam & Bianchi, Robert J. & Mikutowski, Mateusz, 2021. "Long-run reversal in commodity returns: Insights from seven centuries of evidence," Journal of Banking & Finance, Elsevier, vol. 133(C).
    11. Zaremba, Adam & Kizys, Renatas & Raza, Muhammad Wajid, 2020. "The long-run reversal in the long run: Insights from two centuries of international equity returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 177-199.
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    13. Helder Sebastião & Pedro Godinho & Sjur Westgaard, 2020. "Using Machine Learning to Profit on the Risk Premium of the Nordic Electricity Futures," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 67(4), pages 1-17, December.
    14. Hsu, Chih-Hsiang, 2021. "The predictability of the return correlation of futures with different expirations in the Chinese futures market," Resources Policy, Elsevier, vol. 74(C).
    15. Min-Yuh Day & Yensen Ni & Chinning Hsu & Paoyu Huang, 2022. "Do Investment Strategies Matter for Trading Global Clean Energy and Global Energy ETFs?," Energies, MDPI, vol. 15(9), pages 1-15, May.
    16. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    17. Benjamin R. Auer, 2021. "Have trend-following signals in commodity futures markets become less reliable in recent years?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 533-553, December.
    18. Taylor, Nick, 2017. "Timing strategy performance in the crude oil futures market," Energy Economics, Elsevier, vol. 66(C), pages 480-492.

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    More about this item

    Keywords

    Technical trading; Bollinger Bands; Energy futures; Market efficiency;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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