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dc.contributor.authorPesaran, M.H.
dc.date.accessioned2016-08-11T15:25:25Z
dc.date.available2016-08-11T15:25:25Z
dc.date.issued2010-05-29
dc.identifier.otherCWPE1025
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/257184
dc.description.abstractModelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated during the recent financial crisis. We shall examine the nature of asset return correlations using weekly returns on futures markets and investigate the extent to which multivariate volatility models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how adequate these models are for modelling market risk at times of financial crisis. In doing so we consider a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and show that the t-DCC model passes the usual diagnostic tests based on probability integral transforms, but fails the value at risk (VaR) based diagnostics when applied to the post 2007 period that includes the recent financial crisis.en
dc.description.abstract2008 Stock Market Crashen
dc.publisherFaculty of Economics
dc.relation.ispartofseriesCambridge Working Papers in Economics
dc.rightsAll Rights Reserveden
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/en
dc.subjectVolatilities and Correlations
dc.subjectWeekly Returns
dc.subjectMultivariate t
dc.subjectFinancial Interdependence
dc.subjectVaR diagnostics
dc.titleConditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market
dc.typeWorking Paper
dc.identifier.doi10.17863/CAM.1112


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