IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v12y2012i12p1857-1875.html
   My bibliography  Save this article

Quantitative spread trading on crude oil and refined products markets

Author

Listed:
  • Mark Cummins
  • Andrea Bucca

Abstract

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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2012.715749
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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, arXiv.org.
    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.

    More about this item

    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:taf:quantf:v:12:y:2012:i:12:p:1857-1875. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.