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

TitleA high-order Markov-switching model for risk measurement
Authors
Siu, TKChing, WKFung, ENg, MLi, X
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?
DOI: http://dx.doi.org/10.1016/j.camwa.2008.10.099
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
0898-1221
2023 Impact Factor: 2.9
2023 SCImago Journal Rankings: 0.949
ISI Accession Number ID
WOS:000267143100001
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
References in Scopus

 

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.emailChing, WK:wching@hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.description.naturelink_to_OA_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
dc.identifier.issnl0898-1221-

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