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Article: Asset allocation under threshold autoregressive models

TitleAsset allocation under threshold autoregressive models
Authors
KeywordsSTAR model
Asset allocation
Conditional heteroscedasticity
Dynamical programming
Non-linearity
Stochastic dynamical system
SETAR model
Issue Date2012
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/1524-1904/
Citation
Applied Stochastic Models in Business and Industry, 2012, v. 28 n. 1, p. 60-72 How to Cite?
AbstractWe discuss the asset allocation problem in the important class of parametric non-linear time series models called the threshold autoregressive model in (J. Roy. Statist. Soc. Ser. A 1977; 140:34-35; Patten Recognition and Signal Processing. Sijthoff and Noordhoff: Netherlands, 1978; and J. Roy. Statist. Soc. Ser. B 1980; 42:245-292). We consider two specific forms, one self-exciting (i.e. the SETAR model) and the other smooth (i.e. the STAR) model developed by Chan and Tong (J. Time Ser. Anal. 1986; 7:179-190). The problem of maximizing the expected utility of wealth over a planning horizon is considered using a discrete-time dynamic programming approach. This optimization approach is flexible enough to deal with the optimal asset allocation problem under a general stochastic dynamical system, which includes the SETAR model and the STAR model as particular cases. Numerical studies are conducted to demonstrate the practical implementation of the proposed model. We also investigate the impacts of non-linearity in the SETAR and STAR models on the optimal portfolio strategies. Copyright © 2011 John Wiley & Sons, Ltd.
DescriptionResearch article
Persistent Identifierhttp://hdl.handle.net/10722/146396
ISSN
2015 Impact Factor: 0.574
2015 SCImago Journal Rankings: 0.613
ISI Accession Number ID
Funding AgencyGrant Number
RGC7017/07P
HKU
Funding Information:

This research is supported in part by RGC Grants 7017/07P, HKU Strategic Research Theme Fund on Computational Sciences. The authors thank the associate editor and the two anonymous reviewers for their helpful comments and suggestions.

References

 

DC FieldValueLanguage
dc.contributor.authorSong, Nen_HK
dc.contributor.authorSiu, TKen_HK
dc.contributor.authorChing, WKen_HK
dc.contributor.authorTong, Hen_HK
dc.contributor.authorYang, Hen_HK
dc.date.accessioned2012-04-24T07:51:26Z-
dc.date.available2012-04-24T07:51:26Z-
dc.date.issued2012en_HK
dc.identifier.citationApplied Stochastic Models in Business and Industry, 2012, v. 28 n. 1, p. 60-72en_HK
dc.identifier.issn1524-1904en_HK
dc.identifier.urihttp://hdl.handle.net/10722/146396-
dc.descriptionResearch article-
dc.description.abstractWe discuss the asset allocation problem in the important class of parametric non-linear time series models called the threshold autoregressive model in (J. Roy. Statist. Soc. Ser. A 1977; 140:34-35; Patten Recognition and Signal Processing. Sijthoff and Noordhoff: Netherlands, 1978; and J. Roy. Statist. Soc. Ser. B 1980; 42:245-292). We consider two specific forms, one self-exciting (i.e. the SETAR model) and the other smooth (i.e. the STAR) model developed by Chan and Tong (J. Time Ser. Anal. 1986; 7:179-190). The problem of maximizing the expected utility of wealth over a planning horizon is considered using a discrete-time dynamic programming approach. This optimization approach is flexible enough to deal with the optimal asset allocation problem under a general stochastic dynamical system, which includes the SETAR model and the STAR model as particular cases. Numerical studies are conducted to demonstrate the practical implementation of the proposed model. We also investigate the impacts of non-linearity in the SETAR and STAR models on the optimal portfolio strategies. Copyright © 2011 John Wiley & Sons, Ltd.en_HK
dc.languageengen_US
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/1524-1904/en_HK
dc.relation.ispartofApplied Stochastic Models in Business and Industryen_HK
dc.rightsApplied Stochastic Models in Business and Industry. Copyright © John Wiley & Sons Ltd.en_US
dc.subjectSTAR modelen_HK
dc.subjectAsset allocationen_HK
dc.subjectConditional heteroscedasticityen_HK
dc.subjectDynamical programmingen_HK
dc.subjectNon-linearityen_HK
dc.subjectStochastic dynamical systemen_HK
dc.subjectSETAR model-
dc.titleAsset allocation under threshold autoregressive modelsen_HK
dc.typeArticleen_HK
dc.identifier.emailSong, N: smynmath@163.comen_HK
dc.identifier.emailSiu, TK: tksiu@graduate.hku.hken_HK
dc.identifier.emailChing, WK: wching@hku.hk-
dc.identifier.emailTong, H: htong@hku.hk-
dc.identifier.emailYang, H: hlyang@hku.hk-
dc.identifier.authorityChing, WK=rp00679en_HK
dc.identifier.authorityYang, H=rp00826en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1002/asmb.897en_HK
dc.identifier.scopuseid_2-s2.0-84857038909en_HK
dc.identifier.hkuros199184en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84857038909&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume28en_HK
dc.identifier.issue1en_HK
dc.identifier.spage60en_HK
dc.identifier.epage72en_HK
dc.identifier.isiWOS:000300427800004-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridYang, H=7406559537en_HK
dc.identifier.scopusauthoridTong, H=7201359749en_HK
dc.identifier.scopusauthoridChing, WK=13310265500en_HK
dc.identifier.scopusauthoridSiu, TK=8655758200en_HK
dc.identifier.scopusauthoridSong, N=36466983800en_HK

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