Quote from asap:
iv
you could use the variance-covariance model developed by jp morgan (see riskmetrics.com) or monte carlo simulation. i use the latter.
the formula is pretty simple. you have to use the z score for the confidence interval you want to use i.e. 95% the z score is 1.645 times the stdev, assuming normality.
the real challenge is to model the monte carlo simulation rather than calculating var. you have to decide whether you variable follows a normal, discrete or other sort of distribution and then compute multiple simulations. each of those simulations will then be fed into a final distribution in which you'll calculate the var based on the confidence interval that suits you, using nothing more than the stdev and the appropriate z score along with the E(value).