Dynamic dependencies between the Tunisian stock market and other international stock markets: GARCH-EVT-Copula approach

We propose a time-varying copula model to analyse the comovement between the Tunisian stock market and three stock markets: American, French and Moroccan. The model is implemented with a GJR- GARCH-EVT-Copula, which allows capturing nonlinear dependency, tails behaviour and offers significant advantages over econometric techniques in analysing the comovement of financial time series. To capture this dependency structure, we use two time-varying copulas: symmetrized Joe Clayton and Clayton. The time dynamics of the dependency parameter follow those proposed by Patton (2006). We first extract the filtered residuals from each return series with an asymmetric GARCH model, and then we construct the sample marginal cumulative distribution function of each index return using a Gaussian kernel estimate for the interior and a generalized Pareto distribution estimate for the upper and lower tails. A time-varying copula is then fit to the data and used to induce correlation between the simulated residuals of each asset. Empirical results show that the Tunisian stock exchange and the American markets have the greatest dependencies with the French market. Therefore, the managers of portfolios that include assets from these pairs of countries should be particularly concerned about downside risk exposure.