Measuring Value at Risk Under the Conditional Edgeworth-Sargan Distribution

This paper introduces the Edgeworth-Sargan distribution on measuring Value-at-Risk of portfolios. The flexible parametric representation of this density makes it capable of improving the density fits (especially at the tails) and permits a straightforward method of percentile computation. Moreover, the time varying variance-covariance structure of the portfolio can be also estimated consistently to the Edgeworth-Sargan hypothesis since this density admits a straightforward multivariate representation. Estimates of portfolio's VaR evidence the underestimation of VaR measures under the normality assumption and also the more accurate VaR measures under the Edgeworth-Sargan distribution