A general multivariate threshold GARCH model with dynamic conditional correlations

Fabio Trojani () and Francesco Audrino ()

University of St. Gallen Department of Economics working paper series 2005 from Department of Economics, University of St. Gallen

Abstract: We propose a new multivariate DCC-GARCH model that extends existing approaches by admitting multivariate thresholds in conditional volatilities and conditional correlations. Model estimation is numerically feasible in large dimensions and positive semi-definiteness of conditional covariance matrices is naturally ensured by the pure model structure. Conditional thresholds in volatilities and correlations are estimated from the data, together with all other model parameters. We study the performance of our approach in some Monte Carlo simulations, where it is shown that the model is able to fit correctly a GARCH-type dynamics and a complex threshold structure in conditional volatilities and correlations of simulated data. In a real data application to international equity markets, we observe estimated conditional volatilities that are strongly influenced by GARCH-type and multivariate threshold effects. Conditional correlations, instead, are determined by simple threshold structures where no GARCH-type effect could be identified.

JEL-codes: C12 C13 C51 C53 C61 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2005-01
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Working Paper: A general multivariate threshold GARCH model with dynamic conditional correlations (2007)
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