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Time-varying Beta Risk of Pan-European Sectors: A Comparison of Alternative Modeling Techniques

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  • Sascha Mergner

    (AMB Generali Asset Managers)

Abstract

This paper investigates the time-varying behavior of systematic risk for eighteen pan-European industry portfolios. Using weekly data over the period 1987-2005, three different modeling techniques in addition to the standard constant coefficient model are employed: a bivariate t- GARCH(1,1) model, two Kalman filter based approaches as well as a bivariate stochastic volatility model estimated via the efficient Monte Carlo likelihood technique. A comparison of the different models' ex- ante forecast performances indicates that the random-walk process in connection with the Kalman filter is the preferred model to describe and forecast the time-varying behavior of sector betas in a European context.

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File URL: http://128.118.178.162/eps/fin/papers/0509/0509024.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Finance with number 0509024.

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Length: 38 pages
Date of creation: 21 Sep 2005
Date of revision:
Handle: RePEc:wpa:wuwpfi:0509024

Note: Type of Document - pdf; pages: 38. 38 pages, pdf-file
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Web page: http://128.118.178.162

Related research

Keywords: Time-varying beta risk; Kalman filter; bivariate t-GARCH; stochastic volatility; efficient Monte Carlo likelihood; European industry portfolios;

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  1. 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.
  2. 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.
  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. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
  5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  6. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August.
  7. Robert W. Faff & David Hillier & Joseph Hillier, 2000. "Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(5&6), pages 523-554.
  8. 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 116-31, February.
  9. repec:cup:etheor:v:11:y:1995:i:1:p:122-50 is not listed on IDEAS
  10. Braun, Phillip A & Nelson, Daniel B & Sunier, Alain M, 1995. " Good News, Bad News, Volatility, and Betas," Journal of Finance, American Finance Association, vol. 50(5), pages 1575-1603, December.
  11. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
  12. Danielsson, Jon, 1994. "Stochastic volatility in asset prices estimation with simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 375-400.
  13. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
  14. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
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