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p-Hacking: Evidence from Two Million Trading Strategies


  • Tarun Chordia

    (Emory University - Department of Finance)

  • Amit Goyal

    (University of Lausanne)

  • Alessio Saretto

    (University of Texas at Dallas - School of Management - Department of Finance & Managerial Economics)


We implement a data mining approach to generate about 2.1 million trading strategies. This large set of strategies serves as a laboratory to evaluate the seriousness of p-hacking and data snooping in finance. We apply multiple hypothesis testing techniques that account for cross-correlations in signals and returns to produce t-statistic thresholds that control the proportion of false discoveries. We find that the difference in rejections rates produced by single and multiple hypothesis testing is such that most rejections of the null of no outperformance under single hypothesis testing are likely false (i.e., we find a very high rate of type I errors). Combining statistical criteria with economic considerations, we find that a remarkably small number of strategies survive our thorough vetting procedure. Even these surviving strategies have no theoretical underpinnings. Overall, p-hacking is a serious problem and, correcting for it, outperforming trading strategies are rare.

Suggested Citation

  • Tarun Chordia & Amit Goyal & Alessio Saretto, 2017. "p-Hacking: Evidence from Two Million Trading Strategies," Swiss Finance Institute Research Paper Series 17-37, Swiss Finance Institute, revised Apr 2018.
  • Handle: RePEc:chf:rpseri:rp1737

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    Cited by:

    1. Alexander Musaev & Andrey Makshanov & Dmitry Grigoriev, 2022. "Evolutionary Optimization of Control Strategies for Non-Stationary Immersion Environments," Mathematics, MDPI, vol. 10(11), pages 1-17, May.
    2. Alexander Musaev & Andrey Makshanov & Dmitry Grigoriev, 2022. "Numerical Studies of Channel Management Strategies for Nonstationary Immersion Environments: EURUSD Case Study," Mathematics, MDPI, vol. 10(9), pages 1-20, April.

    More about this item


    Hypothesis testing; False discoveries; 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

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