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Quantitative spread trading on crude oil and refined products markets


  • Mark Cummins
  • Andrea Bucca


Quantitative trading in oil-based markets is investigated over 2003--2010, with a focus on WTI, Brent, heating oil and gas oil. A total of 861 spreads are considered. A novel optimal statistical arbitrage trading model is applied, with generalised stepwise procedures controlling for data snooping bias. Aggregating upward and downward mean-reversion, profitable strategies are identified with Sharpe ratios greater than 2 in many instances. For the top categories, average daily returns range from 0.07 to 0.55%, with trade lengths of 9--55 days. A collapse in the number of profitable trading strategies is seen in 2008. Robustness to varying transactions costs is examined.

Suggested Citation

  • 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.
  • Handle: RePEc:taf:quantf:v:12:y:2012:i:12:p:1857-1875
    DOI: 10.1080/14697688.2012.715749

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    Cited by:

    1. Roberto Baviera & Tommaso Santagostino Baldi, 2017. "Stop-loss and Leverage in optimal Statistical Arbitrage with an application to Energy market," Papers 1706.07021,
    2. Krauss, Christopher, 2015. "Statistical arbitrage pairs trading strategies: Review and outlook," FAU Discussion Papers in Economics 09/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    3. Endres, Sylvia & Stübinger, Johannes, 2017. "Optimal trading strategies for Lévy-driven Ornstein-Uhlenbeck processes," FAU Discussion Papers in Economics 17/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    4. Ahmet Göncü, 2015. "Statistical arbitrage in the Black-Scholes framework," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1489-1499, September.
    5. Stübinger, Johannes & Endres, Sylvia, 2017. "Pairs trading with a mean-reverting jump-diffusion model on high-frequency data," FAU Discussion Papers in Economics 10/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    6. Ahmet Göncü & Erdinç Akyıldırım, 2016. "Statistical Arbitrage with Pairs Trading," International Review of Finance, International Review of Finance Ltd., vol. 16(2), pages 307-319, June.
    7. Lubnau, Thorben & Todorova, Neda, 2015. "Trading on mean-reversion in energy futures markets," Energy Economics, Elsevier, vol. 51(C), pages 312-319.
    8. Cummins, Mark, 2013. "EU ETS market interactions: The case for multiple hypothesis testing approaches," Applied Energy, Elsevier, vol. 111(C), pages 701-709.
    9. Kearney, Fearghal & Cummins, Mark & Murphy, Finbarr, 2014. "Outperformance in exchange-traded fund pricing deviations: Generalized control of data snooping bias," Journal of Financial Markets, Elsevier, vol. 19(C), pages 86-109.
    10. Dowling, Michael & Cummins, Mark & Lucey, Brian M., 2016. "Psychological barriers in oil futures markets," Energy Economics, Elsevier, vol. 53(C), pages 293-304.

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