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The Analytic Relationship between Intervaling and Nontrading Effects in Continuous Time

Published online by Cambridge University Press:  06 April 2009

Michael Theobald
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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.

Information

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 18 , Issue 2 , June 1983, pp. 199 - 209
Copyright
Copyright © School of Business Administration, University of Washington 1983

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References

[1]Altman, E.; Jacquillat, B.; and Levasseur, M.. “Comparative Analysis of Risk Measures: France and United States.” Journal of Finance, Vol. 29 (12 1974), pp. 1495–1512.Google Scholar
[2]Beaver, W. “The Information Content of Annual Earnings Announcements.” Journal of Accounting Research, Supplement (1968), pp. 67–92.CrossRefGoogle Scholar
[3]Blattberg, R., and Gonedes, N.. “A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices,” Journal of Business, Vol. 47 (04 1974), pp. 244–280.CrossRefGoogle Scholar
[4]Brown, S., and Warner, J.. “Measuring Security Price Performance.” Journal of Financial Economics, Vol. 8 (09 1980), pp. 205–258.CrossRefGoogle Scholar
[5]Brenner, M. “The Effect of Model Mis-specification on Tests of the Efficient Market Hypothesis.” Journal of Finance, Vol. 32 (03 1977), pp. 57–66.CrossRefGoogle Scholar
[6]Cohen, K.; Hawawini, G.; Maier, S.; Schwartz, R.; and Whitcomb, J.. “Estimating and Adjusting for the Intervaling-Effect Bias in Beta,” Management Science (forthcoming).Google Scholar
[7]Dimson, E. “Risk Measurement When Shares are Subject to Infrequent Trading,” Journal of Financial Economics, Vol. 2 (06, 1979), pp. 197–226.CrossRefGoogle Scholar
[8]Johnston, J. “Econometric Methods.” McGraw-Hill Kogakusha Ltd. (1972).Google Scholar
[9]Levhari, D., and Levy, H.. “The Capital Asset Pricing Model and the Investment Horizon.” Review of Economics and Statistics, Vol. 49 (02 1977), pp. 92–104.CrossRefGoogle Scholar
[10]Marsh, P. “Equity Rights Issues and the Efficiency of the U.K. Stock Market.” Journal of Finance, Vol. 34 (09 1979), pp. 839–862.CrossRefGoogle Scholar
[11]Reinganum, M. “A Direct Test of Roll's Conjecture on the Firm Size Effect” Working paper, University of Southern California (1981).Google Scholar
[12]Roll, R. “A Reply to Mayers and Rice,” Journal of Financial Economics, Vol. 7 (12 1979), pp. 391–400.CrossRefGoogle Scholar
[13]Roll, R. “A Possible Explanation of the Small Firm Effect.” Journal of Finance, Vol. 36 (09 1981), pp. 879–888.CrossRefGoogle Scholar
[14]Scholes, M., and Williams, J.. “Estimating Betas from Non-Synchronous Data.” Journal of Financial Economics, Vol. 5 (12 1977), pp. 309–328.CrossRefGoogle Scholar
[15]Schwartz, R., and Whitcomb, D.. “Evidence of the Presence and Cause of Autocorrelation in Market Model Residuals.” Journal of Financial and Quantitative Analysis, Vol. 12 (06 1977), pp. 291–314.CrossRefGoogle Scholar
[16]Theobald, M. “An Analysis of the Market Model and Beta Factors Using U.K. Equity Share Data.” Journal of Business Finance and Accounting, Vol. 7 (Summer 1980), pp. 49–64.CrossRefGoogle Scholar
[17]Theobald, M., and Thomas, R.. “Time Series Properties of Liquidating Company Equity Returns.” Journal of Banking and Finance (forthcoming).Google Scholar