Risk management research simulation questions
On Monday 28 August 2006 10:40, Joe Byers wrote:
Rmetrics group, I am working on a project to determine the errors associated with structural assumptions underlying a companies Value at Risk calculation. Normal VAR calculations using a covariance matrix for the portfolio assume constant mean or zero mean if the returns are mean adjusted. This project calls for creating 4-5 hypothetical assets, 1 constant mean and variance, 1 seasonal mean and constant variance, 1 constant mean and seasonal variance, 1 time varying mean (AR or Garch in mean), 1 time varying variance (GARCH type). I want to provide the hypothetical parameters for these assets and simulate returns. I can simulate each of these assets as independent but really need correlated errors. These returns will be used to calculate a benchmark risk metrics type VAR and then progess through correcting the VAR calculations for each case of asses type. Anyone that is interested, I would appreciate suggestions. I am also favoring co-authorship for this help.
I've had very good success using Modified Cornish-Fisher VaR to handle the non-normality of the distribution, occasionally with a weighted average of since-inception VaR and rolling period VaR. Why wouldn't you choose existing (real) assets with the characteristics that you want to use in your simulated portfolios? If you want to simulate assets, there are several simulation functions in RMetrics and in other R packages, and I'd suggest that you start there. However, I don't find that these end up looking much like the distributions of real assets in practice, so I don't tend to use them very often. Regards, - Brian