Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?

Tobias Berens, Gregor N.F. Weiß and Dominik Wied

Journal of Empirical Finance, 2015, vol. 32, issue C, 135-152

Abstract: In this paper, we modify the Constant Conditional Correlation (CCC) model and its dynamic counterpart, the Dynamic Conditional Correlation (DCC) model by combining them with a pairwise test for constant correlations, a test for a constant correlation matrix, and a test for a constant covariance matrix. We compare these models to their plain counterparts with respect to the accuracy for forecasting the Value-at-Risk of financial portfolios by a set of distinct backtests. In an empirical horse race of these models based on multivariate portfolios, our study shows that correlation models can be improved by approaches modified by tests for structural breaks in co-movements in several settings.

Keywords: Estimation window; GARCH models; Multivariate time series; Structural breaks; VaR forecasting (search for similar items in EconPapers)
JEL-codes: C32 G17 G32 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:32:y:2015:i:c:p:135-152

DOI: 10.1016/j.jempfin.2015.03.001

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