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dc.contributor.authorBastianin, Andreaen
dc.date.accessioned2011-12-15T11:32:07Z-
dc.date.available2011-12-15T11:32:07Z-
dc.date.issued2009-
dc.identifier.urihttp://hdl.handle.net/10419/53262-
dc.description.abstractIn 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.en
dc.language.isoengen
dc.publisher|aFondazione Eni Enrico Mattei (FEEM) |cMilanoen
dc.relation.ispartofseries|aNota di Lavoro |x24.2009en
dc.subject.jelC32en
dc.subject.jelC52en
dc.subject.jelC53en
dc.subject.jelG17en
dc.subject.jelQ43en
dc.subject.ddc330en
dc.subject.keywordCopula functionsen
dc.subject.keywordForecastingen
dc.subject.keywordValue-At-Risken
dc.titleModelling asymmetric dependence using copula functions: An application to value-at-risk in the energy sector-
dc.typeWorking Paperen
dc.identifier.ppn644985410en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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