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Article: A high-order Markov-switching model for risk measurement

TitleA high-order Markov-switching model for risk measurement
Authors
KeywordsHigher-order Markov chain process
Portfolio
Regime-switching
Risk management
Value-at-Risk
Weak Markov chain process
Issue Date2009
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/camwa
Citation
Computers And Mathematics With Applications, 2009, v. 58 n. 1, p. 1-10 How to Cite?
AbstractIn this paper, we introduce a High-order Markov-Switching (HMS) model for measuring the risk of a portfolio. We suppose that the rate of return from a risky portfolio follows an HMS model with the drift and the volatility modulated by a discrete-time weak Markov chain. The states of the weak Markov chain are interpreted as observable states of an economy. We adopt the Value-at-Risk (VaR) as a metric for market risk quantification and examine the high-order effect of the underlying Markov chain on the risk measures via backtesting. © 2009 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/58951
ISSN
2015 Impact Factor: 1.398
2015 SCImago Journal Rankings: 1.092
ISI Accession Number ID
Funding AgencyGrant Number
RGC7017/07P
HKU Strategic Theme on Computational Sciences and HKU CRGC
HKU Hung Hing Ying Physical Science Research
Funding Information:

The authors would like to thank the anonymous referee for many helpful and constructive comments, suggestions and corrections. Research supported in part by RGC Grant 7017/07P and HKU Strategic Theme on Computational Sciences and HKU CRGC Grant, and in part by HKU Hung Hing Ying Physical Science Research Grant.

References

 

DC FieldValueLanguage
dc.contributor.authorSiu, TKen_HK
dc.contributor.authorChing, WKen_HK
dc.contributor.authorFung, Een_HK
dc.contributor.authorNg, Men_HK
dc.contributor.authorLi, Xen_HK
dc.date.accessioned2010-05-31T03:40:15Z-
dc.date.available2010-05-31T03:40:15Z-
dc.date.issued2009en_HK
dc.identifier.citationComputers And Mathematics With Applications, 2009, v. 58 n. 1, p. 1-10en_HK
dc.identifier.issn0898-1221en_HK
dc.identifier.urihttp://hdl.handle.net/10722/58951-
dc.description.abstractIn this paper, we introduce a High-order Markov-Switching (HMS) model for measuring the risk of a portfolio. We suppose that the rate of return from a risky portfolio follows an HMS model with the drift and the volatility modulated by a discrete-time weak Markov chain. The states of the weak Markov chain are interpreted as observable states of an economy. We adopt the Value-at-Risk (VaR) as a metric for market risk quantification and examine the high-order effect of the underlying Markov chain on the risk measures via backtesting. © 2009 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/camwaen_HK
dc.relation.ispartofComputers and Mathematics with Applicationsen_HK
dc.subjectHigher-order Markov chain processen_HK
dc.subjectPortfolioen_HK
dc.subjectRegime-switchingen_HK
dc.subjectRisk managementen_HK
dc.subjectValue-at-Risken_HK
dc.subjectWeak Markov chain processen_HK
dc.titleA high-order Markov-switching model for risk measurementen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0898-1221&volume=58&spage=1&epage=10&date=2009&atitle=A+high-order+Markov-switching+model+for+risk+measurementen_HK
dc.identifier.emailChing, WK:wching@hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.camwa.2008.10.099en_HK
dc.identifier.scopuseid_2-s2.0-67349216804en_HK
dc.identifier.hkuros155663en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-67349216804&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume58en_HK
dc.identifier.issue1en_HK
dc.identifier.spage1en_HK
dc.identifier.epage10en_HK
dc.identifier.isiWOS:000267143100001-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridSiu, TK=55108012900en_HK
dc.identifier.scopusauthoridChing, WK=13310265500en_HK
dc.identifier.scopusauthoridFung, E=7005440799en_HK
dc.identifier.scopusauthoridNg, M=34571761900en_HK
dc.identifier.scopusauthoridLi, X=27171835600en_HK

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