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.