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A Nonparametric Distribution-Free Test for Serial Independence in Stock Returns: A. Correction

Published online by Cambridge University Press:  06 April 2009

Charles J. Corrado  and
John Schatzberg
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Abstract

A fundamental statistical test of serial independence developed by Ashley and Patterson (1986) to examine a possible form of serial dependence in daily stock returns is shown to be improperly constructed. As a consequence, the significance probabilities that they obtain are overstated. This paper presents a corrected version of their test. The test statistic obtained after correction is shown to possess the same limiting distribution as the Kolmogorov-Smirnov test statistic. Applying the corrected test procedure to data identical to that used by Ashley and Patterson, we find that their original null hypothesis can no longer be rejected at conventional significance levels.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 25 , Issue 3 , September 1990 , pp. 411 - 415
Copyright
Copyright © School of Business Administration, University of Washington 1990

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