Modeling the Dependence of Conditional Correlations on Volatility
Luc Bauwens and
Edoardo Otranto
Working Paper CRENoS from Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia
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 (search for similar items in EconPapers)
Date: 2013
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)
Downloads: (external link)
https://crenos.unica.it/crenos/node/4527
https://crenos.unica.it/crenos/sites/default/files/WP13-04.pdf (application/pdf)
Related works:
Working Paper: Modeling the dependence of conditional correlations on volatility (2013) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cns:cnscwp:201304
Access Statistics for this paper
More papers in Working Paper CRENoS from Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia Contact information at EDIRC.
Bibliographic data for series maintained by CRENoS ().