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Stock Market Forecastability and Volatility: A Statistical Appraisal

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  • N. Gregory Mankiw
  • David Romer
  • Matthew D. Shapiro

Abstract

This paper presents and implements statistical tests of stock market forecastability and volatility that are immune from the severe statistical problems of earlier tests. It finds that although the null hypothesis of market efficiency is rejected, the rejections are only marginal. The paper also shows how volatility tests and recent regression tests are closely related, and demonstrates that when finite sample biases are taken into account, regression tests also fail to provide strong evidence of violations of the conventional valuation model.

Suggested Citation

  • N. Gregory Mankiw & David Romer & Matthew D. Shapiro, 1991. "Stock Market Forecastability and Volatility: A Statistical Appraisal," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 455-477.
    • Handle: RePEc:oup:restud:v:58:y:1991:i:3:p:455-477.
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    File URL: http://hdl.handle.net/10.2307/2298006
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