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Article: Worst-case CVaR based portfolio optimization models with applications to scenario planning

TitleWorst-case CVaR based portfolio optimization models with applications to scenario planning
Authors
KeywordsBox discrete distribution
Conditional value-at-risk (CVaR)
Generation asset
Mixture distribution
Portfolio optimization
Worst-case CVaR (WCVaR)
Issue Date2009
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10556788.asp
Citation
Optimization Methods And Software, 2009, v. 24 n. 6, p. 933-958 How to Cite?
AbstractThis article studies three robust portfolio optimization models under partially known distributions. The proposed models are composed of min-max optimization problems under the worst-case conditional value-at-risk consideration. By using the duality theory, the models are reduced to simple mathematical programming problems where the underlying random variables have a mixture distribution or a box discrete distribution. They become linear programming problems when the loss function is linear. The solutions between the original problems and the reduced ones are proved to be identical. Furthermore, for the mixture distribution, it is shown that the three profit-risk optimization models have the same efficient frontier. The reformulated linear program shows the usability of the method. As an illustration, the robust models are applied to allocations of generation assets in power markets. Numerical simulations confirm the theoretical analysis. © 2009 Taylor & Francis.
Persistent Identifierhttp://hdl.handle.net/10722/58750
ISSN
2015 Impact Factor: 0.841
2015 SCImago Journal Rankings: 1.063
ISI Accession Number ID
Funding AgencyGrant Number
NSF of China10871031
10826099
Educational Department of Human07A001
RGCHKU 719005E
717907E
Hong Kong Research Grant Council
Funding Information:

This work was supported by the NSF of China (10871031, 10826099), the grant from the Educational Department of Human (07A001), the RGC Grant HKU 719005E and 717907E, the Hong Kong Research Grant Council.

References

 

DC FieldValueLanguage
dc.contributor.authorTong, Xen_HK
dc.contributor.authorWu, Fen_HK
dc.contributor.authorQi, Len_HK
dc.date.accessioned2010-05-31T03:36:15Z-
dc.date.available2010-05-31T03:36:15Z-
dc.date.issued2009en_HK
dc.identifier.citationOptimization Methods And Software, 2009, v. 24 n. 6, p. 933-958en_HK
dc.identifier.issn1055-6788en_HK
dc.identifier.urihttp://hdl.handle.net/10722/58750-
dc.description.abstractThis article studies three robust portfolio optimization models under partially known distributions. The proposed models are composed of min-max optimization problems under the worst-case conditional value-at-risk consideration. By using the duality theory, the models are reduced to simple mathematical programming problems where the underlying random variables have a mixture distribution or a box discrete distribution. They become linear programming problems when the loss function is linear. The solutions between the original problems and the reduced ones are proved to be identical. Furthermore, for the mixture distribution, it is shown that the three profit-risk optimization models have the same efficient frontier. The reformulated linear program shows the usability of the method. As an illustration, the robust models are applied to allocations of generation assets in power markets. Numerical simulations confirm the theoretical analysis. © 2009 Taylor & Francis.en_HK
dc.languageengen_HK
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10556788.aspen_HK
dc.relation.ispartofOptimization Methods and Softwareen_HK
dc.subjectBox discrete distributionen_HK
dc.subjectConditional value-at-risk (CVaR)en_HK
dc.subjectGeneration asseten_HK
dc.subjectMixture distributionen_HK
dc.subjectPortfolio optimizationen_HK
dc.subjectWorst-case CVaR (WCVaR)en_HK
dc.titleWorst-case CVaR based portfolio optimization models with applications to scenario planningen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1055-6788&volume=&spage=online, DOI: 10.1080/10556780902865942&epage=&date=2009&atitle=Worst-case+CVaR+based+portfolio+optimization+models+with+applications+to+scenario+planningen_HK
dc.identifier.emailWu, F: ffwu@eee.hku.hken_HK
dc.identifier.authorityWu, F=rp00194en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/10556780902865942en_HK
dc.identifier.scopuseid_2-s2.0-70349614924en_HK
dc.identifier.hkuros162420en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70349614924&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume24en_HK
dc.identifier.issue6en_HK
dc.identifier.spage933en_HK
dc.identifier.epage958en_HK
dc.identifier.isiWOS:000270173300004-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridTong, X=12242993600en_HK
dc.identifier.scopusauthoridWu, F=7403465107en_HK
dc.identifier.scopusauthoridQi, L=7202149952en_HK

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