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A Strategy-Proof Test of Portfolio Returns

Author

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  • Foster, Dean P.
  • Young, H. Peyton

Abstract

Traditional methods for analyzing portfolio returns often rely on multifactor risk assessment, and tests of significance are typically based on variants of the t-test. This approach has serious limitations when analyzing the returns from dynamically traded portfolios that include derivative positions, because standard tests of significance can be 'gamed' using options trading strategies. To deal with this problem we propose a test that assumes nothing about the structure of returns except that they form a martingale difference. Although the test is conservative and corrects for unrealized tail risk, the loss in power is small at high levels of significance.

Suggested Citation

  • Foster, Dean P. & Young, H. Peyton, 2011. "A Strategy-Proof Test of Portfolio Returns," Working Papers 11-50, University of Pennsylvania, Wharton School, Weiss Center.
    • Handle: RePEc:ecl:upafin:11-50
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    File URL: http://fic.wharton.upenn.edu/fic/papers/11/11-50.pdf
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    References listed on IDEAS

    as
    1. Dean P. Foster & H. Peyton Young, 2010. "Gaming Performance Fees By Portfolio Managers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(4), pages 1435-1458.
    2. Wojciech Olszewski & Alvaro Sandroni, 2008. "Manipulability of Future-Independent Tests," Econometrica, Econometric Society, vol. 76(6), pages 1437-1466, November.
    3. Jonathan Ingersoll & Ivo Welch, 2007. "Portfolio Performance Manipulation and Manipulation-proof Performance Measures," The Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1503-1546, 2007 17.
    4. Alvaro Sandroni & Rann Smorodinsky & Rakesh V. Vohra, 2003. "Calibration with Many Checking Rules," Mathematics of Operations Research, INFORMS, vol. 28(1), pages 141-153, February.
    5. Alvaro Sandroni, 2003. "The reproducible properties of correct forecasts," International Journal of Game Theory, Springer;Game Theory Society, vol. 32(1), pages 151-159, December.
    6. Michael Villaverde, 2010. "Measuring investment performance consistency," Quantitative Finance, Taylor & Francis Journals, vol. 10(6), pages 565-574.
    7. Lehrer, Ehud, 2001. "Any Inspection Is Manipulable," Econometrica, Econometric Society, vol. 69(5), pages 1333-1347, September.
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