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Time-Varying Sharpe Ratios and Market Timing

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  • Robert F. Whitelaw

Abstract

This paper documents predictable time-variation in stock market Sharpe ratios. Predetermined financial variables are used to estimate both the conditional mean and volatility of equity returns, and these moments are combined to estimate the conditional Sharpe ratio. In sample, estimated conditional Sharpe ratios show substantial time-variation that coincides with the variation in ex post Sharpe ratios and with the phases of the business cycle. Generally, Sharpe ratios are low at the peak of the cycle and high at the trough. In out-of-sample analysis, using 10-year rolling regressions, we can identify periods in which the ex post Sharpe ratio is approximately three times larger than it full-sample value. Moreover, relatively naïve market-timing strategies that exploit this predictability can generate Sharpe ratios more than 70% larger than a buy-and-hold strategy.

Suggested Citation

  • Robert F. Whitelaw, 1997. "Time-Varying Sharpe Ratios and Market Timing," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-074, New York University, Leonard N. Stern School of Business-.
  • Handle: RePEc:fth:nystfi:98-074
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    Cited by:

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    2. Hanno N. Lustig & Stijn G. Van Nieuwerburgh, 2005. "Housing Collateral, Consumption Insurance, and Risk Premia: An Empirical Perspective," Journal of Finance, American Finance Association, vol. 60(3), pages 1167-1219, June.
    3. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    4. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO.
    5. Qiang Kang, 2019. "Business-cycle pattern of asset returns: a general equilibrium explanation," Annals of Finance, Springer, vol. 15(4), pages 539-561, December.
    6. Peter Woehrmann & Willi Semmler & Martin Lettau, "undated". "Nonparametric Estimation of the Time-varying Sharpe Ratio in Dynamic Asset Pricing Models," IEW - Working Papers 225, Institute for Empirical Research in Economics - University of Zurich.
    7. Peter F. Christoffersen & Francis X. Diebold, 2006. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, INFORMS, vol. 52(8), pages 1273-1287, August.
    8. Hartmann, Daniel & Kempa, Bernd & Pierdzioch, Christian, 2008. "Economic and financial crises and the predictability of U.S. stock returns," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 468-480, June.
    9. Hanno Lustig, 2004. "Housing Collateral, Consumption Insurance and Risk Premia: an Empirical Perspective (joint with Stijn Van Nieuwerburgh), forthcoming Journal of Finance," UCLA Economics Online Papers 300, UCLA Department of Economics.
    10. Hanno Lustig & Stijn Van Nieuwerburgh, 2002. "Housing Collateral, Consumption Insurance and Risk Premia," Macroeconomics 0211008, University Library of Munich, Germany.
    11. Michael A Kelly & Steven P Clark, 2011. "Returns in trading versus non-trading hours: The difference is day and night," Journal of Asset Management, Palgrave Macmillan, vol. 12(2), pages 132-145, June.
    12. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," PIER Working Paper Archive 05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    13. Gabriel Perez‐Quiros & Allan Timmermann, 2000. "Firm Size and Cyclical Variations in Stock Returns," Journal of Finance, American Finance Association, vol. 55(3), pages 1229-1262, June.

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