IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v148y2025ics0140988325004475.html

Mean reversion trading on the naphtha crack

Author

Listed:
  • Turquet, Briac
  • Bajgrowicz, Pierre
  • Scaillet, Olivier

Abstract

We investigate the mean reversion of the naphtha crack after large price moves on daily data over 2014–2024. Our non-parametric estimation of the dynamics of daily price changes assuming a univariate diffusion process shows that the reversion strength increases non-linearly after daily moves exceeding a certain threshold. We perform Monte Carlo simulations to study the duration for which the reversion is likely to remain active. We then backtest corresponding trading strategies. We calibrate parameters of the strategy using grid search while controlling for multiple testing. On average the tested strategies deliver positive returns after transaction costs. We are able to select a subset of outperforming strategies generating robust positive net returns. The existence of positive returns can be explained by differences in liquidity, execution speed, and categories of participants in the naphtha and Brent markets constituting the two legs of the naphtha crack.

Suggested Citation

  • Turquet, Briac & Bajgrowicz, Pierre & Scaillet, Olivier, 2025. "Mean reversion trading on the naphtha crack," Energy Economics, Elsevier, vol. 148(C).
    • Handle: RePEc:eee:eneeco:v:148:y:2025:i:c:s0140988325004475
    DOI: 10.1016/j.eneco.2025.108620
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988325004475
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2025.108620?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    2. Ana Babus & Péter Kondor, 2018. "Trading and Information Diffusion in Over‐the‐Counter Markets," Econometrica, Econometric Society, vol. 86(5), pages 1727-1769, September.
    3. Chris Brooks & Marcel Prokopczuk, 2013. "The dynamics of commodity prices," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 527-542, March.
    4. Murat, Atilim & Tokat, Ekin, 2009. "Forecasting oil price movements with crack spread futures," Energy Economics, Elsevier, vol. 31(1), pages 85-90, January.
    5. Ohana, Steve, 2010. "Modeling global and local dependence in a pair of commodity forward curves with an application to the US natural gas and heating oil markets," Energy Economics, Elsevier, vol. 32(2), pages 373-388, March.
    6. Likai Chen & Ekaterina Smetanina & Wei Biao Wu, 2022. "Estimation of nonstationary nonparametric regression model with multiplicative structure [Income and wealth distribution in macroeconomics: A continuous-time approach]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 176-214.
    7. Torsten Ehlers & Bryan Hardy, 2019. "The evolution of OTC interest rate derivatives markets," BIS Quarterly Review, Bank for International Settlements, December.
    8. Bellia, Mario & Girardi, Giulio & Panzica, Roberto & Pelizzon, Loriana & Peltonen, Tuomas, 2024. "The demand for central clearing: To clear or not to clear, that is the question!," Journal of Financial Stability, Elsevier, vol. 72(C).
    9. 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.
    10. Mahringer, Steffen & Prokopczuk, Marcel, 2015. "An empirical model comparison for valuing crack spread options," Energy Economics, Elsevier, vol. 51(C), pages 177-187.
    11. Lubnau, Thorben & Todorova, Neda, 2015. "Trading on mean-reversion in energy futures markets," Energy Economics, Elsevier, vol. 51(C), pages 312-319.
    12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    13. John Hua Fan & Tingxi Zhang, 2024. "Commodity premia and risk management," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(7), pages 1097-1116, July.
    14. Álvaro Cartea & Patrick Chang & Mateusz Mroczka & Roel Oomen, 2022. "AI-driven liquidity provision in OTC financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 22(12), pages 2171-2204, December.
    15. Taewook Kim & Ha Young Kim, 2019. "Optimizing the Pairs-Trading Strategy Using Deep Reinforcement Learning with Trading and Stop-Loss Boundaries," Complexity, Hindawi, vol. 2019, pages 1-20, November.
    16. Stanton, Richard, 1997. "A Nonparametric Model of Term Structure Dynamics and the Market Price of Interest Rate Risk," Journal of Finance, American Finance Association, vol. 52(5), pages 1973-2002, December.
    17. Holmes, Mark J. & Otero, Jesús & Panagiotidis, Theodore, 2013. "On the dynamics of gasoline market integration in the United States: Evidence from a pair-wise approach," Energy Economics, Elsevier, vol. 36(C), pages 503-510.
    18. Frino, Alex & Ibikunle, Gbenga & Mollica, Vito & Steffen, Tom, 2018. "The impact of commodity benchmarks on derivatives markets: The case of the dated Brent assessment and Brent futures," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 27-43.
    19. Evan Gatev & William N. Goetzmann & K. Geert Rouwenhorst, 2006. "Pairs Trading: Performance of a Relative-Value Arbitrage Rule," The Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 797-827.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    2. Chevallier, Julien & Ielpo, Florian, 2017. "Investigating the leverage effect in commodity markets with a recursive estimation approach," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 763-778.
    3. Bali, Turan G., 2003. "Modeling the stochastic behavior of short-term interest rates: Pricing implications for discount bonds," Journal of Banking & Finance, Elsevier, vol. 27(2), pages 201-228, February.
    4. Weiguang Han & Boyi Zhang & Qianqian Xie & Min Peng & Yanzhao Lai & Jimin Huang, 2023. "Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement Learning," Papers 2301.10724, arXiv.org, revised Feb 2023.
    5. Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2019. "Jumps in commodity markets," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 55-70.
    6. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    7. Psaradellis, Ioannis & Laws, Jason & Pantelous, Athanasios A. & Sermpinis, Georgios, 2023. "Technical analysis, spread trading, and data snooping control," International Journal of Forecasting, Elsevier, vol. 39(1), pages 178-191.
    8. 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).
    9. Lourdes Gómez‐Valle & Ioannis Kyriakou & Julia Martínez‐Rodríguez & Nikos K. Nomikos, 2021. "Estimating risk‐neutral freight rate dynamics: A nonparametric approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1824-1842, November.
    10. 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.
    11. Esposti, Roberto, "undated". "What Makes Commodity Prices Move Together? An Answer From A Dynamic Factor Model," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 260889, European Association of Agricultural Economists.
    12. Rita Pimentel & Morten Risstad & Sjur Westgaard, 2022. "Predicting interest rate distributions using PCA & quantile regression," Digital Finance, Springer, vol. 4(4), pages 291-311, December.
    13. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    14. Chew Lian Chua & Sandy Suardi & Sarantis Tsiaplias, 2011. "Predicting Short-Term Interest Rates: Does Bayesian Model Averaging Provide Forecast Improvement?," Melbourne Institute Working Paper Series wp2011n01, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    15. Arturo Lorenzo-Valdés, 2021. "Conditional Probability of Jumps in Oil Prices," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(4), pages 1-14, Octubre -.
    16. Vazquez, Miguel & Barquín, Julián, 2009. "A fundamental power price model with oligopolistic competition representation," MPRA Paper 15629, University Library of Munich, Germany.
    17. Degenhardt, Thomas & Auer, Benjamin R., 2018. "The “Sell in May” effect: A review and new empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 169-205.
    18. Cheng, Fangzheng & Fan, Tijun & Fan, Dandan & Li, Shanling, 2018. "The prediction of oil price turning points with log-periodic power law and multi-population genetic algorithm," Energy Economics, Elsevier, vol. 72(C), pages 341-355.
    19. Bouezmarni, Taoufik & Rombouts, Jeroen V.K., 2010. "Nonparametric density estimation for positive time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 245-261, February.
    20. Abel Azze & Bernardo D'Auria & Eduardo Garc'ia-Portugu'es, 2022. "Optimal exercise of American options under time-dependent Ornstein-Uhlenbeck processes," Papers 2211.04095, arXiv.org, revised Jun 2024.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:148:y:2025:i:c:s0140988325004475. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.