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A Bayesian Approach to Backtest Overfitting

Author

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  • Jiri Witzany

    () (University of Economics, Faculty of Finance and Accounting, Department of Banking and Insurance, W. Churchill Sq. 4, 130 67, Prague, Czech Republic)

Abstract

Quantitative investment strategies are often selected from a broad class of candidate models estimated and tested on historical data. Standard statistical technique to prevent model overfitting such as out-sample back-testing turns out to be unreliable in the situation when selection is based on results of too many models tested on the holdout sample. There is an ongoing discussion how to estimate the probability of back-test overfitting and adjust the expected performance indicators like Sharpe ratio in order to reflect properly the effect of multiple testing. We propose a consistent Bayesian approach that consistently yields the desired robust estimates based on an MCMC simulation. The approach is tested on a class of technical trading strategies where a seemingly profitable strategy can be selected in the naive approach.

Suggested Citation

  • Jiri Witzany, 2017. "A Bayesian Approach to Backtest Overfitting," Working Papers IES 2017/18, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
  • Handle: RePEc:fau:wpaper:wp2017_18
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    File URL: http://ies.fsv.cuni.cz/sci/publication/show/id/5691/lang/cs
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    More about this item

    Keywords

    Backtest; multiple testing; bootstrapping; cross-validation; probability of backtest overfitting; investment strategy; optimization; Sharpe ratio; Bayesian probability; MCMC;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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