Ricerc@Sapienza

One of the most important issues in finance is to correctly measure the risk
profile of a portfolio, which is fundamental to take optimal decisions on the capital
allocation. In this paper, we deal with the evaluation of portfolio’s Conditional
Value-at-Risk (CVaR) using a modified Gaussian Copula, where the correlation coefficient
is replaced by a generalization of it, obtained as the correlation parameter
of a bivariate Generalized Error Distribution (G.E.D.).We present an algorithm with
the aim of verifying the performance of the G.E.D. method over the classical Risk-
Metrics one, resulting in higher performance of the G.E.D. method.