Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-15T06:59:27.846Z Has data issue: false hasContentIssue false
  • English
  • Français

More on Beta as a Random Coefficient

Published online by Cambridge University Press:  06 April 2009

Gordon J. Alexander  and
P. George Benson
Get access Rights & Permissions [Opens in a new window]

Extract

In their article, “Beta as a Random Coefficient,” Fabozzi and Francis [1] present evidence which suggests that beta is a random coefficient for a “significant minority” of NYSE stocks. They obtained their evidence first, by characterizing the market model as a random coefficient model of the type described by Theil and Mennes [7], and second, by estimating its parameters for a sample of NYSE stocks over the period December 1965 through December 1971. This paper describes weaknesses in Fabozzi and Francis' implementation of the estimation procedures of Theil and Mennes [7] and Hildreth and Houck [3]. Improvements are suggested and utilized in an analysis of the returns of 683 NYSE stocks over the period January I960 through December 1971. The results of the analysis indicate that Fabozzi and Francis have overstated the case for beta being a random coefficient of the form described by Theil and Mennes.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 17 , Issue 1 , March 1982 , pp. 27 - 36
Copyright
Copyright © School of Business Administration, University of Washington 1982

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

[1]Fabozzi, Frank J., and Francis, Jack Clark. “Beta as a Random Coefficient.” Journal of Financial and Quantitative Analysis, Vol. 13 (03 1978), pp. 101–116.CrossRefGoogle Scholar
[2]Froehlich, B. R. “Some Estimators for a Random Coefficient Regression Model.” Journal of the American Statistical Association, Vol. 68 (06 1973), pp. 329–335.Google Scholar
[3]Hildreth, Clifford, and Houck, James P.. “Some Estimators for a Linear Model with Random Coefficients.” Journal of the American Statistical Association, Vol. 63 (06 1968), pp. 584–595.Google Scholar
[4]Kon, S. J., and Lau, W. P.. “Specification Tests for Portfolio Regression Parameter Stationarity and Implications for Empirical Research.” Journal of Finance, Vol. 34 (05 1979), pp. 451–465.Google Scholar
[5]Sunder, S. “Stationarity of Market Risk: Random Coefficient Tests for Individual Common Stocks.” Journal of Finance, Vol. 35 (09 1980), pp. 883–896.CrossRefGoogle Scholar
[6]Theil, Henri. Principles of Econometrics. New York: John Wiley and Sons, Inc. (1971).Google Scholar
[7]Theil, H., and Mennes, L. B. M.. Multiplicative Randomness in Time Series Regression Analysis. Report No. 5901 of the Econometric Institute of the Netherlands School of Economics (1959).Google Scholar
[8]Theil, H., and Van de Panne, C.. “Quadratic Programming as an Extension of Classical Quadratic Maximization.” Management Science, Vol. 7 (10 1960), pp. 1–20.CrossRefGoogle Scholar