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Estimating Value-at-Risk using a Multivariate Copula-Based Volatility Model

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Table 1: Basic statistics of stock returns (in percentages). High excess kurtosis and skewness implies stock returns are not normally distributed.13 URL: http://mc.manuscriptcentral.com/rejf345678910111213141516171819202122232425262728293031323334353637383
Table 2: MLE and copula parameter (in parentheses) values. The best copula that fits the data (in bold) is selected based on the highest MLE value.
Table 3: VaR estimates (in percentages) for the portfolio constructed from returns generated using Archimedean and elliptical copulas.
Table 4: Acceptance region for Basel “traffic light” approach for back-testing VaR models.
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