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Temporary Components of Stock Prices: New Univariate Results

Published online by Cambridge University Press:  06 April 2009

B. Espen Eckbo  and
Jian Liu
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Abstract

While there is growing evidence that stock prices do not follow pure random walks, the degree of existence of temporary components in stock prices is not well known. Modeling stock prices as the sum of a random walk and a general stationary (predictable) component, the paper proposes an estimable lower bound on the proportion of total stock return variance caused by the predictable component. Contrary to the absolute value of the first-order auto-correlation coefficient estimates of Fama and French (1988a), this lower bound reasonably estimates the true variance proportion in finite samples also when the temporary component does not follow a first-order autoregressive process. The estimated mean values of the lower bound reach a maximum of 10 percent for the equal-weighted market portfolio of NYSE stocks over the post-war period 1947–1986, while the maximum is 25 percent for the pre-war period 1926–1946. The value-weighted market portfolio exhibits generally smaller variance proportion estimates. The pure random walk hypothesis is also reexamined using a standard variance ratio statistic extended to multiple return horizons.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 28 , Issue 2 , June 1993 , pp. 161 - 176
Copyright
Copyright © School of Business Administration, University of Washington 1993

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