#### Ashok_Kothavle

##### Member

I do understand the Historical Simulation as well as Var covar method, Especially in VaR Covar mapping of multiple positions into standardized risk factors as well as application of EWMA etc also I am aware. But when it comes to Monte Carlo, I am always confused.

(1) I remember reading in one of Carol Alexander's books on Market Risk (I think mostly Volume no 4 or may be in her discussion forum), she has mentioned that if we assume all the risk factors follow Multivariate Normal Distribution, it doesn't make sense in using Monte Carlo if we are using the Varcovar. The difference in VaR values can be attributed to sampling error.

(2) However, still if I need to use Monte carlo with the underlying assumption that risk factors follow Multivariate Normal Distribution, what Statistical tests I need to check this Multivariate Normal Distribution. Had it been uni-variate, I would have used Kolmogorv Smirnov or Anderson Darling test to check this assumption, but in case of Multivariate distribution, what are the tests?

(3) If at all I need to continue with Monte Carlo with the underlying assumption of Multivariate Normal distribution, how do I use Geometric Brownian Motion (GBM) to compute VaR at say 99%? Do you have some readily available spreadsheet for Monte carlo using GBM?

Regards

Ashok