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On the Diversification, Observability, and Measurement of Estimation Risk

Published online by Cambridge University Press:  06 April 2009

Pete Clarkson ,
Jose Guedes  and
Rex Thompson
Pete Clarkson
Affiliation:
Simon Fraser University, Faculty of Business Administration, Burnaby, British Columbia, CanadaB5A 1S6
Jose Guedes
Affiliation:
Simon Fraser University, Faculty of Business Administration, Burnaby, British Columbia, CanadaB5A 1S6
Rex Thompson
Affiliation:
Southern Methodist University, Cox School of Business, P.O. Box 750333, Dallas, TX 75272
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Abstract

This paper reexamines how risk return relationships are affected by investor uncertainty about the exact parameters of the joint rate of return distribution. We attempt to clarify results relating to three central issues. First, we address the issue of diversification, focusing on an APT, factor model framework. Second, we discuss the observability of estimation risk and describe research experimental designs that should encompass the existence of estimation risk and reveal it in the data. Finally, we suggest exploiting contemporaneous return observations on high and low information securities to aid in the measurement of return parameters for low information securities.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 31 , Issue 1 , March 1996 , pp. 69 - 84
Copyright
Copyright © School of Business Administration, University of Washington 1996

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References

Anderson, T. “Maximum Likelihood Estimates for a Multivariate Normal Distribution when Some Observations are Missing.” Journal of the American Statistical Association, 52 (1957), 200–203.Google Scholar
Barry, C., and Brown, S.. “Differential Information and Security Market Equilibrium.” Journal of Financial and Quantitative Analysis, 20 (12 1985), 407–422.CrossRefGoogle Scholar
Chen, C.-F. “A Bayesian Approach to Nested Missing Data Problems.” In Bayesian Inference and Decision Techniques, Goel, P. and Zellner, A., eds. New York, NY: Elsevier Science Publishers (1986).Google Scholar
Clarkson, P., and Thompson, R.. “The Empirical Estimates of Beta when Investors Face Estimation Risk.” Journal of Finance, 45 (2, 1990), 431–453.CrossRefGoogle Scholar
Coles, J., and Loewenstein, U.. “General Equilibrium and Portfolio Composition in the Presence of Uncertain Parameters and Estimation Risk.” Journal of Financial Economics, 22 (1988), 279–303.CrossRefGoogle Scholar
Coles, J.; Loewenstein, U.; and Suay, J.. “On Equilibrium Pricing under Parameter Uncertainty.” Journal of Financial and Quantitative Analysis, 30 (09 1995), 347–364.Google Scholar
Grinblatt, M., and Titman, S.. “Factor Pricing in a Finite Economy.” Journal of Financial Economics, 12 (1983), 497–508.CrossRefGoogle Scholar
Handa, P., and Linn, S.. “Arbitrage Pricing with Estimation Risk, Journal of Financial and Quantitative Analysis, 28 (03 1993), 81–100.CrossRefGoogle Scholar
Ibbotson, R. “Price Performance of Common Stock New Issues.” Journal of Financial Economics, 2 (1975), 235–272.Google Scholar
Kalymon, B. “Estimation Risk in the Portfolio Selection Model.” Journal of Financial and Quantitative Analysis, 6 (1971), 559–582.Google Scholar
Klein, R., and Bawa, V.. “The Effect of Estimation Risk on Optimal Portfolio Choice.” Journal of Financial Economics, 3 (1976), 215–231.CrossRefGoogle Scholar
Morrison, D.Expectations and Variances of Maximum Likelihood Estimates of the Multivariate Normal Distribution Parameters with Missing Data.” Journal of the American Statistical Association, 66 (1971), 602–604.Google Scholar
Reinganum, M. “Misspecification of Capital Asset Pricing: Empirical Anomalies Based on Earnings' Yields and Market Values.” Journal of Financial Economics, 9 (1981), 19–46.CrossRefGoogle Scholar
Reinganum, M., and Smith, J.. “Investor Preference for Large Firms: New Evidence on Economies of Size.” Journal of Industrial Economics, 32 (1983), 213–227.Google Scholar
Theil, H.Principles of Econometrics. New York, NY: John Wiley & Sons, Inc. (1971).Google Scholar