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Is Time-Series-Based Predictability Evident in Real Time?

Author Info

Listed author(s):
  • Michael Cooper

    (Purdue University)

  • Huseyin Gulen

    (Virginia Tech)

Registered author(s):

    Abstract

    We show that out-of-sample tests used in the time-series predictability literature may suffer from test size problems related to the common practice of exogenous specification of critical parameters, such as the choice of predictive variables, traded assets, and in-sample estimation periods. We perform specification searches across these parameters and find that rejections of the null hypothesis of no predictability are very sensitive to minor variations in parameter specification. We perform simulations to determine if the observed predictability in the data is real. The simulations suggest that much of the literature's out-of-sample evidence of time-series-based predictability is consistent with data snooping.

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    File URL: http://dx.doi.org/10.1086/500676
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    Article provided by University of Chicago Press in its journal Journal of Business.

    Volume (Year): 79 (2006)
    Issue (Month): 3 (May)
    Pages: 1263-1292

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    Handle: RePEc:ucp:jnlbus:v:79:y:2006:i:3:p:1263-1292
    Contact details of provider: Web page: http://www.journals.uchicago.edu/JB/

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    Cited by:

    1. Ahmad, Mashood & Ali, Syed Babar, 2008. "Technical Analysis in the Stock Markets of Pakistan: A Case of Commercial Banks," MPRA Paper 64521, University Library of Munich, Germany.
    2. Pierdzioch, Christian & Reitz, Stefan & Ruelke, Jan-Christoph, 2015. "Heteroeneous forecasters and nonlinear expectation formation in US stock market," FinMaP-Working Papers 29, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Pierdzioch, Christian & Reitz, Stefan & Ruelke, Jan-Christoph, 2014. "Heterogeneous Forecasters and Nonlinear Expectation Formation in the U.S. Stock Market," FinMaP-Working Papers 11, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    4. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    5. Stefano Gubellini, 2014. "Conditioning information and cross-sectional anomalies," Review of Quantitative Finance and Accounting, Springer, vol. 43(3), pages 529-569, October.
    6. Reitz, Stefan & Pierdzioch, Christian & Rülke, Jan-Christoph, 2015. "Nonlinear Expectation Formation in the U.S. Stock Market," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113210, Verein für Socialpolitik / German Economic Association.
    7. Pierdzioch, Christian & Reitz, Stefan & Ruelke, Jan-Christoph, 2015. "Nonlinear expectation formation in the U.S. stock market: Empirical evidence from the Livingston survey," Kiel Working Papers 1947 [rev.], Kiel Institute for the World Economy (IfW).
    8. Campbell R. Harvey & Yan Liu & Heqing Zhu, 2014. ". . . and the Cross-Section of Expected Returns," NBER Working Papers 20592, National Bureau of Economic Research, Inc.
    9. Barras, Laurent, 2007. "International conditional asset allocation under specification uncertainty," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 443-464, September.
    10. Fang, Jiali & Jacobsen, Ben & Qin, Yafeng, 2014. "Predictability of the simple technical trading rules: An out-of-sample test," Review of Financial Economics, Elsevier, vol. 23(1), pages 30-45.
    11. Granziera, Eleonora & Hubrich, Kirstin & Moon, Hyungsik Roger, 2014. "A predictability test for a small number of nested models," Journal of Econometrics, Elsevier, vol. 182(1), pages 174-185.
    12. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
    13. Han, Yufeng, 2012. "State uncertainty in stock markets: How big is the impact on the cost of equity?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2575-2592.
    14. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2015. "Market Sentiment and Paradigm Shifts," Research Paper Series 356, Quantitative Finance Research Centre, University of Technology, Sydney.
    15. Byrne, Joseph & Fu, Rong, 2016. "Stock Return Prediction with Fully Flexible Models and Coefficients," MPRA Paper 75366, University Library of Munich, Germany.

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