Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/18342
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dc.contributor.advisorPandey, Ajay
dc.contributor.authorKhnadelia, Ritu
dc.contributor.authorSarin, Vikram
dc.date.accessioned2016-08-19T10:41:18Z
dc.date.available2016-08-19T10:41:18Z
dc.date.copyright2002
dc.date.issued2002
dc.identifier.urihttp://hdl.handle.net/11718/18342
dc.description.abstractAbsrtact Value at risk provides a single measure in dollars of a firm's potential losses. It makes a statement of the kind: "We are X percent certain that we will not lose more than V doilars in the nest N days". Here n represents the time most commonly used approach to VaR calculation is the JP Morgan Risk Metrics approach. However this method assumes constant volatility and lack of dependence between volatility and correlation. The paper proves that in fact when volatilities of indices increase the correlation between them also increases. This has the effect of increasing the VaR values and decreasing diversification benefits. As such the JP Morgan approach underestimates the VaR valur. An alternative solution could be the use of GARCH (1,1) model that incorporates the effects of time varying volatility thereby yielding more accurate result.en_US
dc.language.isoenen_US
dc.publisherIndian Institute of Management Ahmedabaden_US
dc.relation.ispartofseriesSP;000978
dc.subjectRisk calculationen_US
dc.subjectDiversification benefitsen_US
dc.subjectLinear modelen_US
dc.subjectRisk metricsen_US
dc.subject(EWMA)en_US
dc.subjectGARCH (1,1) modelen_US
dc.subjectCirculation of VaRen_US
dc.titleValue at risk calculation and diversification benefitsen_US
dc.typeStudent Projecten_US
Appears in Collections:Student Projects

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