The aim of this dissertation is to analyze how the subprime crisis impacted the dependence structure among the emerging and developed markets by using the MSCI (Morgan Stanley Capital International) market index as proxy for each of these markets. The proposed methodology is based on the construction of bivariate distributions via conditional copulas. The marginal distribution for each of the indexes makes use of univariate GARCH models and model dependence is captured via the following copulas: normal, normal GAS (Generalised Autoregressive Score) and Joe-Clayton symmetric considering both fixed parameters (static framework) and time varying parameters (dynamic framework). Our results show that the normal GAS copula with structural break was the most adequate to capture dependence between the returns of emerging and developed markets. Throughout the proposed framework it was possible to infer that correlation and tail dependence measures between these markets sharply increased during the subprime crisis. Finally VaR (Value at Risk) coverage was used as goodness of fit measure, and on this metric the normal GAS copula has also outperformed the others.