The Copula-GARCH Model of Conditional Dependencies:
An International Stock Market Application
Eric Jondeau and Michael Rockinger*
Journal of International Money and Finance, 2006, 25(5), 827-853.
Abstract
Modeling the dependency between stock-market returns is a difficult task when
returns follow a complicated dynamics. When returns are non-normal, it is often
simply impossible to specify the multivariate distribution relating two or more
return series. In this context, we propose a new methodology based on copula
functions, which consists in estimating first the univariate distributions and
then the joining distribution. In such a context, the dependency parameter can
easily be rendered conditional and time-varying. We apply this methodology to
the daily returns of four major stock markets. Our results suggest that conditional
dependency depends on past realizations for European market pairs only. For
these markets, dependency is found to be more widely affected when returns move
in the same direction than when they move in opposite direction. Modeling the
dynamics of the dependency parameter also suggests that dependency is higher
and more persistent between European stock markets.
Keywords: Stock indices, International correlation, Dependency, GARCH model,
Skewed Student-t distribution, Copula function.
JEL classification: C51, F37, G11.
* HEC Lausanne