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The Journal of Portfolio Management

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The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest
Overfitting, and Non-Normality

David H. Bailey and Marcos López de Prado
The Journal of Portfolio Management Special 40th Anniversary Issue 2014, 40 (5) 94-107; DOI: https://doi.org/10.3905/jpm.2014.40.5.094
David H. Bailey
recently retired from Lawrence Berkeley National Laboratory in Berkeley, CA, and is a research fellow in the Department of Computer Science at the University of California in Davis, CA.
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  • For correspondence: david@davidhbailey.com
Marcos López de Prado
is senior managing director at Guggenheim Partners in New York, NY, and a research fellow at Lawrence Berkeley National Laboratory in Berkeley, CA.
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  • For correspondence: lopezdeprado@lbl.gov
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Abstract

With the advent in recent years of large financial data sets, machine learning, and high-performance computing, analysts can back test millions (if not billions) of alternative investment strategies. Backtest optimizers search for combinations of parameters that maximize the simulated historical performance of a strategy, leading to back test overfitting. The problem of performance inflation extends beyond back testing. More generally, researchers and investment managers tend to report only positive outcomes, a phenomenon known as selection bias. Not controlling for the number of trials involved in a particular discovery leads to overly optimistic performance expectations. The deflated Sharpe ratio (DSR) corrects for two leading sources of performance inflation: Selection bias under multiple testing and non-normally distributed returns. In doing so, DSR helps separate legitimate empirical findings from statistical flukes.

TOPICS: Big data/machine learning, factor-based models, statistical methods

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The Journal of Portfolio Management: 40 (5)
The Journal of Portfolio Management
Vol. 40, Issue 5
Special 40th Anniversary Issue 2014
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The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest
Overfitting, and Non-Normality
David H. Bailey, Marcos López de Prado
The Journal of Portfolio Management Sep 2014, 40 (5) 94-107; DOI: 10.3905/jpm.2014.40.5.094

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The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest
Overfitting, and Non-Normality
David H. Bailey, Marcos López de Prado
The Journal of Portfolio Management Sep 2014, 40 (5) 94-107; DOI: 10.3905/jpm.2014.40.5.094
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Jump to section

  • Article
    • Abstract
    • MULTIPLE TESTING
    • SELECTION BIAS
    • BACKTEST OVERFITTING
    • AN ONLINE TOOL TO EXPLORE BACKTEST OVERFITTING
    • BACKTEST OVERFITTING UNDER MEMORY EFFECTS
    • BACKTEST OVERFITTING AND THE HOLDOUT METHOD
    • GENERAL APPROACHES TO MULTIPLE TESTING
    • EXPECTED SHARPE RATIOS UNDER MULTIPLE TRIALS
    • THE DEFLATED SHARPE RATIO
    • A NUMERICAL EXAMPLE
    • WHEN SHOULD WE STOP TESTING?
    • CONCLUSIONS
    • APPENDIX A
    • APPENDIX B
    • APPENDIX C
    • ENDNOTES
    • REFERENCES
  • Info & Metrics
  • PDF

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