using mgarch to estimate value at risk

in this paper we compared multivariate garch models toestimate value at risk. we used a portfolio of weekly indexesincluding tedpix klse xu100 during ten years. to estimatevalue at risk first we estimated ccc dcc of engle dcc of tseand tsui dynamic equi correlation models by oxmetrics. then optimum lags were estimated by minimizing the information criteria.to estimate var the models accuracy was validated by usingvariance covariance matrix. the results show that although cccmodel estimates variance matrix better dynamic equi correlation ispreferable to estimate value at risk employing more completecorrelation matrix.