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Conditionally parametric fits for CAPM betas

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  • Abberger, Klaus

Abstract

The CAPM model assumes stock returns to be a linear function of the market return. However, there is considerable evidence that the beta stability assumption commonly used when estimating the model is invalid. Nonparametric regression methods are used to examine the stability of beta coefficients in German stock returns. Since local polynomial regression is used for estimation, known methods for testing the stability and for bandwidth choice can be used. For some returns the test indicates time-varying betas. For these returns conditionally parametric fits are calculated.

Suggested Citation

  • Abberger, Klaus, 2004. "Conditionally parametric fits for CAPM betas," CoFE Discussion Papers 04/04, University of Konstanz, Center of Finance and Econometrics (CoFE).
    • Handle: RePEc:zbw:cofedp:0404
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    File URL: https://www.econstor.eu/bitstream/10419/23566/1/dp04_04.pdf
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    1. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    2. Joseph Cheng, 1997. "A switching regression approach to the stationarity of systematic and non-systematic risks: the Hong Kong experience," Applied Financial Economics, Taylor & Francis Journals, vol. 7(1), pages 45-57.
    3. Bos, T & Newbold, P, 1984. "An Empirical Investigation of the Possibility of Stochastic Systematic Risk in the Market Model," The Journal of Business, University of Chicago Press, vol. 57(1), pages 35-41, January.
    4. Fabozzi, Frank J. & Francis, Jack Clark, 1978. "Beta as a Random Coefficient," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 13(1), pages 101-116, March.
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