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The Analytic Relationship between Intervaling and Nontrading Effects in Continuous Time
Published online by Cambridge University Press: 06 April 2009
Extract
Empirical studies in finance generally use data defined over the shortest return period available. Originally, data bases such as CRSP, tended to have data collected over monthly periods and most analyses tended to use monthly data rather than data compounded over periods greater than a month with the implicit argument that the more data the “better”. Since the development of data bases with data collected over shorter differencing intervals, there has been a growing tendency in finance to use returns data defined over increasingly shorter differencing intervals. This development is desirable, but is not without problems. The problem with using data defined over shorter differencing intervals is that, although greater estimating efficiency will be achieved, nontrading effects could be introduced into the analysis. These will lead to biased beta estimators and biases in tests of capital market efficiency. The purpose of this paper is to investigate, analytically, the interrelation of the intervaling and nontrading effects both in estimating beta factors and in testing capital market efficiency.
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- Copyright © School of Business Administration, University of Washington 1983
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