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Modeling the dependence of conditional correlations on volatility

Luc Bauwens () and Edoardo Otranto ()

No 2013014, CORE Discussion Papers from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: Several models have been developed to capture the dynamics of the conditional correlations between time series of financial returns, but few studies have investigated the determinants of the correlation dynamics. A common opinion is that the market volatility is a major determinant of the correlations. We extend some models to capture explicitly the dependence of the correlations on the volatility of the market of interest. The models differ in the way by which the volatility influences the correlations, which can be transmitted through linear or nonlinear, and direct or indirect effects. They are applied to different data sets to verify the presence and possible regularity of the volatility impact on correlations.

Keywords: volatility effects; conditional correlation; DCC; Markov switching (search for similar items in EconPapers)
JEL-codes: C32 C58 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets
Date: 2013-05-06
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Working Paper: Modeling the Dependence of Conditional Correlations on Volatility (2013) Downloads
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