Time-Varying Mixture GARCH Models and Asymmetric Volatility

Markus Haas, Jochen Krause, Marc S. Paolella and Sven C. Steude
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Jochen Krause: University of Zürich
Marc S. Paolella: University of Zurich, Ecole Polytechnique Fédérale de Lausanne, and Swiss Finance Institute
Sven C. Steude: University of Zürich

No 13-04, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: The class of mixed normal conditional heteroskedastic (MixN-GARCH) models, which couples a mixed normal distributional structure with GARCH-type dynamics, has been shown to offer a plausible decomposition of the contributions to volatility, as well as excellent out-of-sample forecasting performance, for financial asset returns. In this paper, we generalize the MixN-GARCH model by relaxing the assumption of constant mixing weights. Two different specifications with time-varying mixing weights are considered. In particular, by relating current weights to past returns and realized (component-wise) likelihood values, an empirically reasonable representation of Engle and Ng's (1993) news impact curve with an asymmetric impact of unexpected return shocks on future volatility is obtained. An empirical out-of-sample study confirms the usefulness of the new approach and gives evidence that the leverage effect in financial returns data is closely connected, in a non-linear fashion, to the time-varying interplay of mixture components representing, for example, various groups of market participants.

Keywords: GARCH; News Impact Curve; Leverage Effect; Down-Market Effect; Mixtures; Time-Varying Weights; Value-at-Risk (search for similar items in EconPapers)
JEL-codes: C22 C51 G10 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2013-01
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Citations: View citations in EconPapers (11)

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Journal Article: Time-varying mixture GARCH models and asymmetric volatility (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp1304

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