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Expectations for Statistical Arbitrage in Energy Futures Markets

Author

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  • Tadahiro Nakajima

    (The Kansai Electric Power Company, Incorporated, 6-16, Nakanoshima 3-chome, Kita-Ku, Osaka 530-8270, Japan
    Graduate School of Economics, Kobe University, 2-1 Rokkodai-cho Nada-ku, Kobe 657-8501, Japan)

Abstract

Energy futures have become important as alternative investment assets to minimize the volatility of portfolio return, owing to their low links with traditional financial markets. In order to make energy futures markets grow further, it is necessary to expand expectations of returns from trading in energy futures markets. Therefore, this study examines whether profits can be earned by statistical arbitrage between wholesale electricity futures and natural gas futures listed on the New York Mercantile Exchange. On the assumption that power prices and natural gas prices have a cointegration relationship, as tested and supported by previous studies, the short-term deviation from the long-term equilibrium is regarded as an arbitrage opportunity. The results of the spark-spread trading simulations using historical data from 2 January 2014 to 29 December 2017 show about 30% yield at maximum. This study shows the possibility of generating earnings in energy futures market.

Suggested Citation

  • Tadahiro Nakajima, 2019. "Expectations for Statistical Arbitrage in Energy Futures Markets," JRFM, MDPI, vol. 12(1), pages 1-12, January.
    • Handle: RePEc:gam:jjrfmx:v:12:y:2019:i:1:p:14-:d:197788
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    References listed on IDEAS

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    Cited by:

    1. Tadahiro Nakajima & Yuki Toyoshima, 2019. "Measurement of Connectedness and Frequency Dynamics in Global Natural Gas Markets," Energies, MDPI, vol. 12(20), pages 1-15, October.
    2. Tadahiro Nakajima & Yuki Toyoshima, 2020. "Examination of the Spillover Effects among Natural Gas and Wholesale Electricity Markets Using Their Futures with Different Maturities and Spot Prices," Energies, MDPI, vol. 13(7), pages 1-14, March.
    3. Johannes Stübinger & Lucas Schneider, 2019. "Statistical Arbitrage with Mean-Reverting Overnight Price Gaps on High-Frequency Data of the S&P 500," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    4. Matsumoto, Takuji & Yamada, Yuji, 2021. "Simultaneous hedging strategy for price and volume risks in electricity businesses using energy and weather derivatives1," Energy Economics, Elsevier, vol. 95(C).
    5. Fabian Waldow & Matthias Schnaubelt & Christopher Krauss & Thomas Günter Fischer, 2021. "Machine Learning in Futures Markets," JRFM, MDPI, vol. 14(3), pages 1-14, March.
    6. Kasper Johansson & Thomas Schmelzer & Stephen Boyd, 2024. "A Markowitz Approach to Managing a Dynamic Basket of Moving-Band Statistical Arbitrages," Papers 2412.02660, arXiv.org.
    7. Kasper Johansson & Thomas Schmelzer & Stephen Boyd, 2024. "Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization," Papers 2402.08108, arXiv.org.
    8. Shigeyuki Hamori, 2020. "Empirical Finance," JRFM, MDPI, vol. 13(1), pages 1-3, January.

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