Using MGARCH to Estimate Value at Risk

Document Type : Research Paper


1 Assistant Prof., Finance, Alzahra University, Tehran, Iran

2 M.Sc., Finance, Alzahra University, Tehran, Iran


In this paper we compared multivariate GARCH models to
estimate Value-at-Risk. We used a portfolio of weekly indexes
including TEDPIX, KLSE, XU100 during ten years. To estimate
Value-at-Risk, first we estimated CCC, DCC of Engle, DCC of Tse
and 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 using
variance-covariance matrix. The results show that although CCC
model estimates variance matrix better, Dynamic Equi correlation is
preferable to estimate Value-at-Risk, employing more complete
correlation matrix.


Main Subjects