Review of Economic Studies Vol. 58 No. 3 1991

Stock Market Forecastability and Volatility: A Statistical Appraisal

N. Gregory Mankiw¹; David Romer²; Matthew D. Shapiro^3,4

¹ Harvard University · ² University of California, Berkeley · ³ University of Michigan–Ann Arbor · ⁴ Michigan United

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.

DOI

10.2307/2298006

Volume

58

Issue

3

Pages

455

Sources

bibtex:phds-export.bib openalex crossref

Cite

APA 7 MLA 9 Chicago (author–date) Harvard Elsevier Harvard (JFE, JBF…) The Accounting Review Academy of Management American Marketing Association INFORMS (Management Science) Copy citation Copied ✓