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Structural analysis of portfolio risk using beta impulse response functions

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  • C. M. Hafner
  • H. Herwartz

Abstract

We estimate the data generating process of daily excess returns of 20 major German stocks in a CAPM framework with time varying betas. Our sample spans a 23 year period from 1974 to 1996. An asymmetric dependence of volatility on lagged innovations is taken into account. We introduce beta impulse response functions to shed light on the structural implications of systematic risk associated with competing volatility models. The dependence of beta on news is characterized with respect to different sources (asset specific vs. market general news). The empirical results suggest that negative news emerging from the market involve a stronger impact on beta relative to positive news. Concerning firm specific news the opposite relation is found for the majority of the analysed data sets.

Suggested Citation

  • C. M. Hafner & H. Herwartz, 1998. "Structural analysis of portfolio risk using beta impulse response functions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 52(3), pages 336-355, November.
    • Handle: RePEc:bla:stanee:v:52:y:1998:i:3:p:336-355
    DOI: 10.1111/1467-9574.00088
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    Cited by:

    1. Helmut Herwartz & Helmut Lütkepohl, 2000. "Multivariate volatility analysis of VW stock prices," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 9(1), pages 35-54, March.
    2. Christian M. Hafner & Helmut Herwartz, 2008. "Testing for Causality in Variance Usinf Multivariate GARCH Models," Annals of Economics and Statistics, GENES, issue 89, pages 215-241.
    3. Hafner, Christian M., 2000. "Fourth moments of multivariate GARCH processes," SFB 373 Discussion Papers 2000,80, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Hafner, Christian M. & Herwartz, Helmut, 2001. "Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis," Journal of Empirical Finance, Elsevier, vol. 8(1), pages 1-34, March.
    5. Wolfgang Haerdle & Helmut Herwartz & Volodia Spokoiny, 2000. "Time Inhomogeneous Multiple Volatility Modelling," Econometric Society World Congress 2000 Contributed Papers 1429, Econometric Society.
    6. Jelena Z. Minović & Boško R. Živković, 2010. "Open Issues In Testing Liquidity In Frontier Financial Markets: The Case Of Serbia," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 55(185), pages 33-62, April - J.
    7. Hyeong-Ohk Bae & Seung-Yeal Ha & Yongsik Kim & Hyuncheul Lim & Jane Yoo, 2020. "Volatility Flocking by Cucker–Smale Mechanism in Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(3), pages 387-414, September.

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