Transformational Approach to Analytical Value-at-Risk for near Normal Distributions

In this paper, we extend the parametric approach of VaR estimation that is based upon application two transforms, one for handling skewness and other kurtosis. These transformations restore normality to data when applied in succession. The transforms are well defined offer an alternative models on variance–covariance approach. We demonstrate technique using three pairs uncorrelated but negatively skewed fat-tailed stock return distributions, pair each from recent periods US international market, stressed period economic history. Furthermore, analysis domain by calculating expected shortfalls risk capital under different methods. For sake completion, compare results normal transformation methods non-parametric historical simulation.