Modeling the Dependence of Conditional Correlations on Market Volatility

Luc Bauwens and Edoardo Otranto

Journal of Business & Economic Statistics, 2016, vol. 34, issue 2, 254-268

Abstract: Several models have been developed to capture the dynamics of the conditional correlations between time series of financial returns and several studies have shown that the market volatility is a major determinant of the correlations. We extend some models to include explicitly the dependence of the correlations on the market volatility. The models differ by the way—linear or nonlinear, direct or indirect—in which the volatility influences the correlations. Using a wide set of models with two measures of market volatility on two datasets, we find that for some models, the empirical results support to some extent the statistical significance and the economic significance of the volatility effect on the correlations, but the presence of the volatility effect does not improve the forecasting performance of the extended models. Supplementary materials for this article are available online.

Date: 2016
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Citations: View citations in EconPapers (21)

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Working Paper: Modeling the dependence of conditional correlations on market volatility (2016)
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DOI: 10.1080/07350015.2015.1037882

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