Time-varying mixture GARCH models and asymmetric volatility

Markus Haas, Jochen Krause, Marc S. Paolella and Sven C. Steude

The North American Journal of Economics and Finance, 2013, vol. 26, issue C, 602-623

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)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:26:y:2013:i:c:p:602-623

DOI: 10.1016/j.najef.2013.02.024

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