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Optimized pairs-trading strategies in the cryptocurrencies market using genetic algorithms and cointegration

Author

Listed:
  • Lorette DANILO

    (PhD Student, Univ Rennes, CNRS, CREM – UMR6211, F-35000 Rennes France)

  • Fayssal JAMHAMED

    (Quantitative Portfolio Manager, Federal Finance Gestion)

  • Franck MARTIN

    (Professor, Univ Rennes, CNRS, CREM – UMR6211, F-35000 Rennes France)

Abstract

Cryptoassets market is notoriously volatile and risky. In this context, marketneutral type strategies, such as pair-trading, may be relevant. In this article, we focus on the implementation of pair-trading strategies with a wide range of cryptoassets (209) over a period halved from 2021-08-01 to 2024-01-31. To carry out this study, we combine econometric and machine learning techniques to stand out from the existing literature. By using cointegration tests and error correction models, we identify a final sample of 229 pairs suitable for pair-trading strategies. Using a genetic algorithm and pair clustering, we test four strategies employing standard and optimized thresholds. The results highlight the existence of profitable cointegrating relationships and therefore short-term market inefficiencies in the cryptoassets market. Indeed, the best strategy identified in terms of risk-return couple, although it remains risky with a median maxdrawdown of 29%, delivers an average annual Sharpe ratio per pair of 1.53 over the backtesting period.

Suggested Citation

  • Lorette DANILO & Fayssal JAMHAMED & Franck MARTIN, 2024. "Optimized pairs-trading strategies in the cryptocurrencies market using genetic algorithms and cointegration," Economics Working Paper Archive (University of Rennes & University of Caen) 2024-11, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    • Handle: RePEc:tut:cremwp:2024-11
    as

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    References listed on IDEAS

    as
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    3. Dang, Chao & Chen, Xinyang & Yu, Shengjie & Chen, Rongda & Yang, Yifan, 2022. "Credit ratings of Chinese households using factor scores and K-means clustering method," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 309-320.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Cryptoassets; Pair-trading; Cointegration; Error-correction models; Genetic algorithm; Bollinger bands; Short-term market inefficiencies;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • 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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