[R-SIG-Finance] Multivariate random number generation for skewed distribution of asset class returns

shawn tan @h@wntkh93 @end|ng |rom y@hoo@com@@g
Tue Jan 14 15:31:36 CET 2020

Hi R-SIG-Finance mailing list,
I have a query about performing a Monte Carlo random number generation for asset class returns which accounts for the distribution of the asset class (mean, variance, skewness and possibly kurtosis) while also taking into consideration the correlation/covariance matrix of the asset classes. 
I came across the R package, mvtnorm, which is able to take the asset classes' means, covariance matrix for a normal distribution, through the function rmvnorm(n, mean = muvec, sigma = covmat), where n is number of trials, mean is the mean vector and sigma is the covariance matrix. However, this package does not allow for a skewed distribution or excess kurtosis. Historical data for my asset class returns show both positive and negative skewness. Additionally, the Johnson distribution function in R package, SuppDists, does not seem to account for covariances as inputs.
Hence, is there an R package/function that allows me to perform the random number generation for multivariate returns, which accounts for mean, variance, correlation, skewness and even kurtosis as inputs under the Monte Carlo simulation?
Thank you
Best regards,
	[[alternative HTML version deleted]]

More information about the R-SIG-Finance mailing list