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Time-Varying Betas of German Stock Returns

  • Markus Ebner

    ()

  • Thorsten Neumann

    ()

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    The market 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 market model is invalid. In this paper we account for beta instability in German stock returns by allowing the coefficients to vary over time in estimation. For time-varying beta estimation we rely on the Flexible Least Squares approach, the Random Walk Model and Moving Window Least Squares. Due to our results time-varying estimation fits the data considerably better than time-invariant estimation and, hence, increases the efficiency of beta based risk measurement. Copyright Swiss Society for Financial Market Research 2005

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    File URL: http://hdl.handle.net/10.1007/s11408-005-2296-5
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    Article provided by Springer in its journal Financial Markets and Portfolio Management.

    Volume (Year): 19 (2005)
    Issue (Month): 1 (June)
    Pages: 29-46

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    Handle: RePEc:kap:fmktpm:v:19:y:2005:i:1:p:29-46
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    1. Brooks, Robert D. & Faff, Robert W. & Lee, John H. H., 1994. "Beta stability and portfolio formation," Pacific-Basin Finance Journal, Elsevier, vol. 2(4), pages 463-479, December.
    2. Lutkepohl, Helmut & Herwartz, Helmut, 1996. "Specification of varying coefficient time series models via generalized flexible least squares," Journal of Econometrics, Elsevier, vol. 70(1), pages 261-290, January.
    3. Helmut LÜTKEPOHL & Martin MORYSON & Jürgen WOLTERS, 1994. "Stabilitaetsanalyse der bundesdeutschen Geldnachfrage anhand alternativer Ansaetze zur Modellierung variierender Regressionskoeffizienten," SFB 373 Discussion Papers 1994,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Kalaba, Robert E. & Tesfatsion, Leigh S., 1989. "Time-Varying Linear Regression Via Flexible Least Squares," Staff General Research Papers 11196, Iowa State University, Department of Economics.
    5. Tesfatsion, Leigh & Veitch, John M., 1990. "U.S. money demand instability A flexible least squares approach," Journal of Economic Dynamics and Control, Elsevier, vol. 14(1), pages 151-173, February.
    6. Alexander, Gordon J. & Benson, P. George & Eger, Carol E., 1982. "Timing Decisions and the Behavior of Mutual Fund Systematic Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 17(04), pages 579-602, November.
    7. Chauveau, T. & Maillet, B., 1998. "Flexible Least Squares Betas: The French Market Case," Papers 1998-03/fi, Caisse des Depots et Consignations - Cahiers de recherche.
    8. Chow, Gregory C., 1984. "Random and changing coefficient models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 21, pages 1213-1245 Elsevier.
    9. Schwert, G William & Seguin, Paul J, 1990. " Heteroskedasticity in Stock Returns," Journal of Finance, American Finance Association, vol. 45(4), pages 1129-55, September.
    10. Sunder, Shyam, 1980. " Stationarity of Market Risk: Random Coefficients Tests for Individual Stocks," Journal of Finance, American Finance Association, vol. 35(4), pages 883-96, September.
    11. Collins, Daniel W & Ledolter, Johannes & Rayburn, Judy Dawson, 1987. "Some Further Evidence on the Stochastic Properties of Systematic Risk," The Journal of Business, University of Chicago Press, vol. 60(3), pages 425-48, July.
    12. Fabozzi, Frank J. & Francis, Jack Clark, 1978. "Beta as a Random Coefficient," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 13(01), pages 101-116, March.
    13. Martin MORYSON, 1994. "Testing for Random Walk Coefficients in a Simple State Space Model," SFB 373 Discussion Papers 1994,21, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
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