File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A Markovian infectious model for dependent default risk

TitleA Markovian infectious model for dependent default risk
Authors
KeywordsDependent default risk
Markovian infectious models
Common shocks
Multi-sector modelling
Chain reaction
Issue Date2011
PublisherInderscience Publishers. The Journal's web site is located at http://www.inderscience.com/IJIEI
Citation
International Journal of Intelligent Engineering Informatics, 2011, v. 1 n. 2, p. 174-195 How to Cite?
AbstractModelling dependent defaults has long been a central issue for credit risk measurement and management. To address this important issue, we introduce a Markovian infectious model to describe the dependent relationship of default processes of credit securities. The central tenant of the proposed model is the concept of common shocks which is one of the major approaches to describe insurance risk. Using real data default data, we compare the proposed model to some existing default risk models, such as one-sector and two-sector models discussed in Ching et al. (2008, 2010). A log likelihood ratio test is adopted for the purpose of model comparison. Our empirical results reveal that the proposed model outperforms both the one-sector and two-sector models. We also illustrate the application of the proposed model for quantitative risk measurement. In particular, numerical results for both the crisis value-at-risk and the crisis expected shortfall are provided.
Persistent Identifierhttp://hdl.handle.net/10722/133627
ISSN

 

DC FieldValueLanguage
dc.contributor.authorGu, JWen_US
dc.contributor.authorChing, WKen_US
dc.contributor.authorSiu, TKen_US
dc.date.accessioned2011-05-24T02:12:20Z-
dc.date.available2011-05-24T02:12:20Z-
dc.date.issued2011en_US
dc.identifier.citationInternational Journal of Intelligent Engineering Informatics, 2011, v. 1 n. 2, p. 174-195en_US
dc.identifier.issn1758-8715-
dc.identifier.urihttp://hdl.handle.net/10722/133627-
dc.description.abstractModelling dependent defaults has long been a central issue for credit risk measurement and management. To address this important issue, we introduce a Markovian infectious model to describe the dependent relationship of default processes of credit securities. The central tenant of the proposed model is the concept of common shocks which is one of the major approaches to describe insurance risk. Using real data default data, we compare the proposed model to some existing default risk models, such as one-sector and two-sector models discussed in Ching et al. (2008, 2010). A log likelihood ratio test is adopted for the purpose of model comparison. Our empirical results reveal that the proposed model outperforms both the one-sector and two-sector models. We also illustrate the application of the proposed model for quantitative risk measurement. In particular, numerical results for both the crisis value-at-risk and the crisis expected shortfall are provided.-
dc.languageengen_US
dc.publisherInderscience Publishers. The Journal's web site is located at http://www.inderscience.com/IJIEI-
dc.relation.ispartofInternational Journal of Intelligent Engineering Informaticsen_US
dc.rightsInternational Journal of Intelligent Engineering Informatics. Copyright © Inderscience Publishers.-
dc.subjectDependent default risk-
dc.subjectMarkovian infectious models-
dc.subjectCommon shocks-
dc.subjectMulti-sector modelling-
dc.subjectChain reaction-
dc.titleA Markovian infectious model for dependent default risken_US
dc.typeArticleen_US
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1758-8715&volume=1&issue=2&spage=174&epage=195&date=2011&atitle=A+Markovian+Infectious+Model+for+Dependent+Default+Risk-
dc.identifier.emailChing, WK: wching@hku.hken_US
dc.identifier.emailSiu, TK: ken.siu@efs.mq.edu.auen_US
dc.identifier.doi10.1504/IJIEI.2011.040178-
dc.identifier.hkuros185364en_US
dc.identifier.volume1en_US
dc.identifier.issue2-
dc.identifier.spage174en_US
dc.identifier.epage195en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats