I want to thank everyone that posted replies to this question. You have provided insight and helped me clarify how to proceed with this project, along with some additional ideas to incorporate, like the modified cornish VAR. When I get this project to a complete working paper, I will gladly provide it to you. Thank you Joe
Joe Byers wrote:
I want to simulate hypothetical assets so I can control all aspects of the tests, from parameters to correlations across assets. I can construct correlations based on minimum variance hedge ratios that will allow me to create hedge portfolios with higher weights on some assets than others. This way I can also look at hedging aspects within the VAR calculation and the problems with violating the models assumptions. I have used garchsim and armasim, but as I understand their implementation, I am simulating the independent process, not a correlated process. Including the modified cornish VAR is a really good idea as a benchmark case as well. thanks for that suggestion, if nothing else you are entitled to a footnote for it. Thanx Joe Brian G. Peterson wrote:
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