Message-ID: <532058447.2459603.1445845624626.JavaMail.yahoo@mail.yahoo.com>
Date: 2015-10-26T07:47:04Z
From: Amelia Marsh
Subject: Monte Carlo Convergence test
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 regards
Amelia