[R-SIG-Finance] calibration of GARCH models to futures data

[Ivette]

 I have done the usual estimation of GARCH models with R, applied to my
historical dataset (commodities futures) with a maximum likelihood function
and selected the best model on the basis of information criteria (AIC, BIC). 

 Can somebody explain me  the calibration scheme for a GARCH model with
futures data? 

 I was not able to find a paper, dealing with exactly this algorithm for my
case. I only understood from the unrelated calibration literature that in
general I have to compare the performance of the best model (from the
estimation step), fitted to my historical dataset and a  simulation (let's
abbreviate this Squared Error difference to "E2"). 

 However, it is not clear to me: 
 - with what parameters' values to start this simulation, 
 - how many times it is normal to perform it, 
 - what to compare via E2 (maximum likelihood values, or parameter values) 
 - how to construct & assess E2 for the GARCH case. 

 Thank you in advance for your suggestions. 
 
 Ivette


--
View this message in context: http://r.789695.n4.nabble.com/calibration-of-GARCH-models-to-futures-data-tp4603646.html
Sent from the Rmetrics mailing list archive at Nabble.com.