Stock Market Forecastability and Volatility: A Statistical Appraisal

N. Gregory Mankiw (), David Romer () and Matthew D. Shapiro

Review of Economic Studies, 1991, vol. 58, issue 3, pages 455-77

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. Copyright 1991 by The Review of Economic Studies Limited.

Date: 1991
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Related works:
Working Paper: STOCK MARKET FORECASTABILITY AND VOLATILITY: A STATISTICAL APPRAISAL (1989)
Working Paper: Stock Market Forecastability and Volatility: A Statistical Appraisal (1989)
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