Modelling Asymmetric Dependence Using Copula Functions: An Application to Value-at-Risk in the Energy Sector
Andrea Bastianin ()
No 50452, Sustainable Development Papers from Fondazione Eni Enrico Mattei (FEEM)
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 findings confirm the importance of nonnormalities and asymmetries both in-sample and out-of-sample.
Keywords: Risk; and; Uncertainty (search for similar items in EconPapers)
References: Add references at CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
Working Paper: Modelling Asymmetric Dependence Using Copula Functions: An application to Value-at-Risk in the Energy Sector (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ags:feemdp:50452
Access Statistics for this paper
More papers in Sustainable Development Papers from Fondazione Eni Enrico Mattei (FEEM) Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().