Time-Varying Mixture GARCH Models and Asymmetric Volatility

26 Pages Posted: 10 Mar 2013

See all articles by Markus Haas

Markus Haas

University of Kiel - Faculty of Economics and Social Sciences

Jochen Krause

University of Zurich - Department of Banking and Finance

Marc S. Paolella

University of Zurich - Department of Banking and Finance; Swiss Finance Institute

Sven C. Steude

University of Zurich - Department of Banking and Finance

Date Written: January 23, 2013

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

JEL Classification: C22, C51, G10

Suggested Citation

Haas, Markus and Krause, Jochen and Paolella, Marc S. and Steude, Sven Christian, Time-Varying Mixture GARCH Models and Asymmetric Volatility (January 23, 2013). Swiss Finance Institute Research Paper No. 13-04, Available at SSRN: https://ssrn.com/abstract=2229740 or http://dx.doi.org/10.2139/ssrn.2229740

Markus Haas

University of Kiel - Faculty of Economics and Social Sciences ( email )

Kiel
Germany

Jochen Krause

University of Zurich - Department of Banking and Finance ( email )

Schönberggasse 1
Zürich, 8001
Switzerland
+41446342814 (Phone)

HOME PAGE: http://www.bf.uzh.ch

Marc S. Paolella (Contact Author)

University of Zurich - Department of Banking and Finance

Plattenstr. 14
Zürich, 8032
Switzerland

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Sven Christian Steude

University of Zurich - Department of Banking and Finance ( email )

Plattenstrasse 32
Zürich, CH-8032
Switzerland

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