The development of financial markets requires the introduction of new models, forecasting and risk management. One of the indicators that are considered in risk management and measurement is value at risk index. In this research, the multivariate GARCH model has been ev
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The development of financial markets requires the introduction of new models, forecasting and risk management. One of the indicators that are considered in risk management and measurement is value at risk index. In this research, the multivariate GARCH model has been evaluated to predict the value of exposed portfolio risk, including currency, stocks and gold, and the combined returns of gold price data, total stock exchange index and exchange rates from 2009 to 2016 were used. The results of VECH, BEKK, DCC, and VECH diagonal models have shown that the volatility of these variables in the estimation period is effective and this confirms the hypothesis of market independence in Iran, in order to evaluate the performance of these models in predicting VAR One-day prediction of conditional variance covariance matrix of models was used. The results of the post-test of the models using the coup and kristoferson tests showed the performance of all four models was appropriate and the comparison of the mean loss function of Lopez showed that the VECH model had better performance than other models. Despite the good performance of the VECH model, however, the estimation of this model is very time-consuming. due to the large number of parameters that are estimated in the estimation of VECH and BEKK models that lead to a reduction in the degree of freedom and, as a result, a reduction in the validity of the model, the use of these two models for portfolios with more than three assets is not recommended.
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