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Testing for Predictability in Conditionally Heteroskedastic Stock Returns

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  • Joakim Westerlund
  • Paresh Narayan

Abstract

The difficulty of predicting stock returns has recently motivated researchers to start looking for more powerful tests, and the current study takes a step in this direction. Unlike existing tests, the test proposed here exploits the information contained in the heteroskedasticity of findings, which is expected to lead to higher power, a result that is confirmed by our results. In order to also maintain good size accuracy, subsample critical values are used.

Suggested Citation

  • Joakim Westerlund & Paresh Narayan, 2015. "Testing for Predictability in Conditionally Heteroskedastic Stock Returns," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 342-375.
    • Handle: RePEc:oup:jfinec:v:13:y:2015:i:2:p:342-375.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbu001
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    Keywords

    predictability; FQGLS; conditional heteroskedasticity; subsampling; stock returns;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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