Forecasting Volatility for an Optimal Portfolio with Stylized Facts Using Copulas

In this paper, we seek to examine the effect of the presence of stylized facts on forecasting volatility and we model the dependence between exchange rate returns using a flexible approach that allows us to investigate whether the co-movement of the different stylized facts on portfolio optimization. First,we focus on the dependence structure using copulas. The empirical results show that the co-jumps, long memory, leverage effects affect the dependence structure. Second, we analyze the impact of the presence of stylized facts with the dependence structure using Gumbel copula on the optimal portfolio. We propose a new approach to forecasting volatility portfolio with dynamic factor models including stylized facts and assuming that the dependence structure is modeled by the copula parameter. The empirical results show that our approach outperforms the basic models without stylized facts and where the dependence structure is represented by the linear correlation coefficient.