Abstract:
Dependence between financial markets is a key concern for investors who seek to diversify their
portfolios as they manage risks arising as a result of their investment decisions. In this paper we
apply the copula theory to model dependence between the equity and the exchange rate markets
of Kenya. We use the Semi Parametric Copula Based Multivariate Dynamical (SCOMDY) model
proposed by (Chen and Fan, 2006) to estimate the dependence between these two markets.
Using the moving window maximum likelihood estimation technique, we extend the SCOMDY
estimator to capture time variation in the dependence. Our findings point to symmetric
dependence in the markets. Amongst the parametric copula models fitted into the data, the t
copula with 10 degrees of freedom is found to be the most appropriate for capturing the static
dependence over the entire study period. Extreme value dependence is also present in the
bivariate series whereby both markets rise and fall during periods of boom and bust. The
hypothesis of homogeneity in dependence is rejected in all but three trading periods, pointing to
the insufficiency of static parametric copula models to capture the dependence.
