Confidence intervals for multivariate value at risk - Goh, Y. L.; Pooi, Ah Hin * (2012)
Confidence intervals for the y-quantile of a linear combination of N non-normal variates with a linear dependence structure would be useful to the financial institutions as the intervals enable the accuracy of the value at risk (VaR) of a portfolio of investments to be quantified. Presently, we construct 100(1-α) % confidence intervals for the y-quantile using the procedures based on bootstrap, normal approximation and hypothesis testing. We show that the method based on hypothesis testing produces confidence interval which is more satisfactory than those found by using bootstrap or normal approximation.