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Volatility models with innovations from new maximum entropy densities at work

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  • Fischer, Matthias J.
  • Gao, Yang
  • Herrmann, Klaus

Abstract

Generalized autoregressive conditional heteroskedasticity (GARCH) processes have become very popular as models for financial return data because they are able to capture volatility clustering as well as leptokurtic unconditional distributions which result from the assumption of conditionally normal error distributions. In contrast, Bollerslev (1987) and several follow-ups provided evidence that starting with leptokurtic and possibly skewed (conditional) error distributions will achieve better results. Parallel to these exible but to some extend arbitrary chosen parametric distributions, recent years saw a rise in suggestions for maximum entropy distributions (e.g. Rockinger and Jondeau, 2002, Park and Bera, 2009 or Fischer and Herrmann, 2010). Within this contribution we provide a comprehensive comparison between both different ME densities and their parametric competitors within different generalized GARCH models such as APARCH and GJR-GARCH.

Suggested Citation

  • Fischer, Matthias J. & Gao, Yang & Herrmann, Klaus, 2010. "Volatility models with innovations from new maximum entropy densities at work," FAU Discussion Papers in Economics 03/2010, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  • Handle: RePEc:zbw:iwqwdp:032010
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    Cited by:

    1. Schnitzlein, Daniel D., 2012. "How important is cultural background for the level of intergenerational mobility?," Economics Letters, Elsevier, vol. 114(3), pages 335-337.
    2. Tinkl, Fabian, 2010. "A note on Hadamard differentiability and differentiability in quadratic mean," FAU Discussion Papers in Economics 08/2010, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.

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    Keywords

    GARCH; APARCH; Entropy density; Skewness; Kurtosis;

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