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German Stock Market Dynamics

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  • Bauer, Rob M M J
  • Nieuwland, Frederick G M C
  • Verschoor, Willem F C

Abstract

This article estimates generalized ARCH (GARCH) models for German stock market indices returns, using weekly and monthly data, various GARCH specifications and (non)normal error densities, and a variety of diagnostic checks. German stock return series exhibit significant levels of second-order dependence. Our results clearly demonstrate that for both weekly as well as monthly return series, the Student-t distribution is superior to the standard normal distribution. In particular, the estimated GARCH-t models appear to be reasonably successful in accounting for both observed leptokurtosis and conditional heteroskedasticy from German stock return movements.

Suggested Citation

  • Bauer, Rob M M J & Nieuwland, Frederick G M C & Verschoor, Willem F C, 1994. "German Stock Market Dynamics," Empirical Economics, Springer, vol. 19(3), pages 397-418.
    • Handle: RePEc:spr:empeco:v:19:y:1994:i:3:p:397-418
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    Cited by:

    1. Rob Bauer & Fred Nieuwland, 1995. "A multiplicative model for volume and volatility," Applied Mathematical Finance, Taylor & Francis Journals, vol. 2(3), pages 135-154.
    2. Jung, Robert C. & Liesenfeld, Roman, 1996. "Testing the bivariate mixture hypothesis using German stock market data," Tübinger Diskussionsbeiträge 67, University of Tübingen, School of Business and Economics.

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