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Programming Language Choices for Algo Traders: The Case of Pairs Trading

Author

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  • Pedro Vergel Eleuterio

    (Birkbeck, University of London)

  • Lovjit Thukral

    (JP Morgan Asset Management)

Abstract

In the last 20 years, relative value strategies have increased in popularity in various asset classes, including equity and commodity markets. Due to an increase in market participants, more sophisticated algorithms than those used in the past are now required to generate excess returns in pairs trading strategies. Sophisticated algorithms can cause an increase in complexity which, in-turn, increases computational run time. In our pairs trading example, C++ provides the best performance, however, it is also the most time consuming to implement. Among the languages that allow for faster development, Cython provides the best balance between run times and ease of prototyping.

Suggested Citation

  • Pedro Vergel Eleuterio & Lovjit Thukral, 2019. "Programming Language Choices for Algo Traders: The Case of Pairs Trading," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1443-1449, April.
    • Handle: RePEc:kap:compec:v:53:y:2019:i:4:d:10.1007_s10614-018-9813-x
    DOI: 10.1007/s10614-018-9813-x
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    References listed on IDEAS

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    1. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    2. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    3. 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.
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    More about this item

    Keywords

    Programming language; Performance; Pairs trading; Trading strategies;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • 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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