Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models

dc.contributor.authorAsai, M.
dc.contributor.authorCaporin, M.
dc.contributor.authorMcAleer, M.
dc.date.accessioned2012-03-19T20:50:17Z
dc.date.available2012-03-19T20:50:17Z
dc.date.issued2012en
dc.descriptionRePeC Working Paper Series: 04/12en
dc.description.abstractMost multivariate variance or volatility models suffer from a common problem, the "curse of dimensionality". For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on multivariate models with milder restrictions, whose purpose was to combine the need for interpretability and efficiency faced by model users with the computational problems that may emerge when the number of assets is quite large. We contribute to this strand of the literature proposing a block-type parameterization for multivariate stochastic volatility models. The empirical analysis on stock returns on US market shows that 1% and 5 % Value-at-Risk thresholds based on one-step-ahead forecasts of covariances by the new specification are satisfactory for the period includes the global financial crisis.en
dc.identifier.citationAsai, M., Caporin, M., McAleer, M. (2012) Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models. Department of Economics and Finance. 37pp..en
dc.identifier.urihttp://hdl.handle.net/10092/6439
dc.language.isoen
dc.publisherCollege of Business and Economicsen
dc.publisherUniversity of Canterbury. Department of Economics and Financeen
dc.relation.urihttp://www.econ.canterbury.ac.nz/RePEc/cbt/econwp/1204.pdfen
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subjectblock structuresen
dc.subjectmultivariate stochastic volatilityen
dc.subjectcurse of dimensionalityen
dc.subjectleverage effectsen
dc.subjectmulti-factorsen
dc.subjectheavy-tailed distributionen
dc.subject.anzsrcFields of Research::35 - Commerce, management, tourism and services::3502 - Banking, finance and investment::350208 - Investment and risk managementen
dc.subject.anzsrcFields of Research::38 - Economics::3802 - Econometrics::380202 - Econometric and statistical methodsen
dc.titleForecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Modelsen
dc.typeDiscussion / Working Papers
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