Correlated ARCH (CorrARCH): Modelling the time-varying conditional correlation between financial asset returns

Correlated ARCH (CorrARCH): Modelling the time-varying conditional correlation between financial asset returns

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Article ID: iaor20023536
Country: Netherlands
Volume: 139
Issue: 2
Start Page Number: 351
End Page Number: 370
Publication Date: Jun 2002
Journal: European Journal of Operational Research
Authors: ,
Abstract:

Although the time variation of the conditional correlations of asset returns is a well established stylized fact (and of crucial importance for efficient financial decisions) there is no explicit general model available for its estimation and forecasting. In this paper, we propose a bivariate GARCH covariance structure in which conditional variances can follow any GARCH-type process, while conditional correlation is generated by an explicit discrete-time stochastic process, the CorrARCH process. A high order CorrARCH can parsimoniously be represented by a CorGARCH process. The model successfully generates the reported stylized facts, establishes an autocorrelation structure for correlations and thus provides an explicit framework for out-of-sample forecasting. We provide empirical evidence from the G7 Stock Market Indexes.

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