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Modeling the dependency between stock market returns is a difficult task when returns follow a complicated dynamics. It is not easy to specify the multivariate distribution relating two or more return series. In this paper, a methodology based on fitting ARIMA, GARCH and ARMA-GARCH models and copula functions is applied. In such methodology, the dependency parameter can easily be rendered conditional and time varying. This method is used to the daily returns of five major stock markets (Telecomdoi:10.5281/zenodo.3334136 fatcat:3qhhsxf2j5dczi4aykebxlu56i