Dear Forum, I have series of say 100 (say equity) instrument prices. From these prices, for each of these 100 instruments, I generate returns using ln(current price / previous price). Assuming originally I had 251 prices available for each of these 100 instruments over last one year period, I have matrix of 250X100 returns. I assume that these returns follow Multivariate Normal Distribution. Using the returns, I generate a mean Vector of returns 'M' and also generate the Variance - covariance matrix of returns 'S'. Then using MASS library, I simulate say 10000 returns for each of the 100 instruments as : sim_rates = mvrnorm(10000, M, S) This gives me 10000 simulated returns for each of the 100 instruments and using these simulated returns carry out further analysis. My query is how do I carry out convergence test in R to arrive at sufficint number of simulations? With reagrds Amelia