Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/12057
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dc.contributor.authorBhattacharyya, Malay-
dc.contributor.authorRamkumar, Siddarth Madhav-
dc.date.accessioned2020-05-05T14:15:55Z-
dc.date.available2020-05-05T14:15:55Z-
dc.date.issued2012-
dc.identifier.issn2162-2434-
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/12057-
dc.description.abstractThe paper presents and tests Dynamic Value at Risk (VaR) estimation procedures for equity index returns. Volatility clustering and leptokurtosis are well-documented characteristics of such time series. An ARMA (1, 1)-GARCH (1, 1) approach models the inherent autocorrelation and dynamic volatility. Fattailed behavior is modeled in two ways. In the first approach, the ARMA-GARCH process is run assuming alternatively that the standardized residuals are distributed with Pearson Type IV, Johnson SU, Manly’s exponential transformation, normal and t-distributions. In the second approach, the ARMA-GARCH process is run with the pseudonormal assumption, the parameters calculated with the pseudo maximum likelihood procedure, and the standardized residuals are later alternatively modeled with Mixture of Normal distributions, Extreme Value Theory and other power transformations such as John-Draper, Bickel-Doksum, Manly, Yeo-Johnson and certain combinations of the above. The first approach yields five models, and the second ap-proach yields nine. These are tested with six equity index return time series using rolling windows. These models are compared by computing the 99%, 97.5% and 95% VaR violations and contrasting them with the expected number of violations.-
dc.publisherScientific Research Publishing-
dc.subjectDynamic VaR-
dc.subjectGARCH-
dc.subjectEVT-
dc.subjectJohnson SU-
dc.subjectPearson Type IV-
dc.subjectMixture of Normal Distributions-
dc.subjectManly-
dc.subjectJohn Draper-
dc.subjectYeo-Johnson Transformations-
dc.titleA comparison of VaR estimation procedures for Leptokurtic equity index returns-
dc.typeJournal Article-
dc.identifier.doi10.4236/jmf.2012.21002-
dc.pages13-30p.-
dc.vol.noVol.2-
dc.issue.noIss.1-
dc.journal.nameJournal of Mathematical Finance-
Appears in Collections:2010-2019
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