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Modelling Asymmetric Dependence Using Copula Functions: An Application to Value-at-Risk in the Energy Sector
Company: Fondazione Eni Enrico Mattei
Year Of Publication: 2009
Month Of Publication: June
Download Count: 12
View Count: 2014
Comment Num: 0
Language: English
Who Can Read: Free
Date: 5-14-2010
Publisher: Administrator
In this paper I have used copula functions to forecast the Value-at-Risk (VaR) of an equally weighted portfolio comprising a small cap stock index and a large cap stock index for the oil and gas industry. The following empirical questions have been analyzed: (i) are there nonnormalities in the marginals, (ii) are there nonnormalities in the dependence structure, (iii) is it worth modelling these nonnormalities in risk- management applications, (iv) do complicated models perform better than simple models. As for questions (i) and (ii) I have shown that the data do deviate from the null of normality at the univariate, as well as at the multivariate level. When considering the dependence structure of the data I have found that asymmetries show up in their unconditional distribution, as well as in their unconditional copula. The VaR forecasting exercise has shown that models based on Normal marginals and/or with symmetric dependence structure fail to deliver accurate VaR forecasts. These
Bastianin, Andrea Sign in to follow this author
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