Conditional Copula-GARCH Methods for Value at Risk of Portfolio
Combining Copula and Forecasting Function of GARCH Model to Estimate of Portfolio's Value at Risk
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Value at risk (VaR) is one of the most important criteria for risk measuring, which is often used at financial institutions for risk measuring.The VaR is largely used to measure the risk of a portfolio. One of the main difficulties in estimating VaR is to model the dependence structure, especially because VaR is concerned with the tail of the distribution. There are several approaches for the estimation of VaR, such as the variance-covariance, the historical simulation and the Monte Carlo approaches. The analytical approach has been largely used after the publishing of the Risk-metrics methodo...
Value at risk (VaR) is one of the most important criteria for risk measuring, which is often used at financial institutions for risk measuring.The VaR is largely used to measure the risk of a portfolio. One of the main difficulties in estimating VaR is to model the dependence structure, especially because VaR is concerned with the tail of the distribution. There are several approaches for the estimation of VaR, such as the variance-covariance, the historical simulation and the Monte Carlo approaches. The analytical approach has been largely used after the publishing of the Risk-metrics methodology. This approach adopts the assumption of multivariate normality of the joint distribution of the assets returns. The covariance matrix is a natural measure of dependence between the assets and the variance is a good measure of risk. In finance the normality is rarely an adequate assumption. The deviation from normality could lead to an inadequate VaR estimate. In this case, the portfoliocould be either riskier than desired or the financial institution unnecessarily conservative.
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