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Article: On some models for value-at-risk
Title | On some models for value-at-risk | ||||||||
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Authors | |||||||||
Keywords | GARCH model Mixtures Threshold models Value-at-risk | ||||||||
Issue Date | 2010 | ||||||||
Publisher | Taylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/07474938.asp | ||||||||
Citation | Econometric Reviews, 2010, v. 29 n. 5, p. 622-641 How to Cite? | ||||||||
Abstract | The idea of statistical learning can be applied in financial risk management. In recent years, value-at-risk (VaR) has become the standard tool for market risk measurement and management. For better VaR estimation, Engle and Manganelli (2004) introduced the conditional autoregressive value-at-risk (CAViaR) model to estimate the VaR directly by quantile regression. To entertain the nonlinearity and structural change in the VaR, we extend the CAViaR idea using two approaches: the threshold GARCH (TGARCH) and the mixture-GARCH models. The estimation method of these models are proposed. Our models should possess all the advantages of the CAViaR model and enhance the nonlinear structure. The methods are applied to the S&P500, Hang Seng, Nikkei and Nasdaq indices to illustrate our models. © Taylor & Francis Group, LLC. | ||||||||
Persistent Identifier | http://hdl.handle.net/10722/125401 | ||||||||
ISSN | 2023 Impact Factor: 0.8 2023 SCImago Journal Rankings: 1.051 | ||||||||
ISI Accession Number ID |
Funding Information: Philip L. H. Yu would like to thank a small project fund from the University of Hong Kong for partial support. W. K. Li would like to thank the Croucher Foundation for awarding a Senior Research Fellowship (2003-2004) and the Hong Kong Research Grant Council grant HKU7036/06P for partial support. The authors would also like to thank two referees for their valuable advices. | ||||||||
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yu, PLH | en_HK |
dc.contributor.author | Li, WK | en_HK |
dc.contributor.author | Jin, S | en_HK |
dc.date.accessioned | 2010-10-31T11:29:19Z | - |
dc.date.available | 2010-10-31T11:29:19Z | - |
dc.date.issued | 2010 | en_HK |
dc.identifier.citation | Econometric Reviews, 2010, v. 29 n. 5, p. 622-641 | en_HK |
dc.identifier.issn | 0747-4938 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/125401 | - |
dc.description.abstract | The idea of statistical learning can be applied in financial risk management. In recent years, value-at-risk (VaR) has become the standard tool for market risk measurement and management. For better VaR estimation, Engle and Manganelli (2004) introduced the conditional autoregressive value-at-risk (CAViaR) model to estimate the VaR directly by quantile regression. To entertain the nonlinearity and structural change in the VaR, we extend the CAViaR idea using two approaches: the threshold GARCH (TGARCH) and the mixture-GARCH models. The estimation method of these models are proposed. Our models should possess all the advantages of the CAViaR model and enhance the nonlinear structure. The methods are applied to the S&P500, Hang Seng, Nikkei and Nasdaq indices to illustrate our models. © Taylor & Francis Group, LLC. | en_HK |
dc.language | eng | en_HK |
dc.publisher | Taylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/07474938.asp | en_HK |
dc.relation.ispartof | Econometric Reviews | en_HK |
dc.subject | GARCH model | en_HK |
dc.subject | Mixtures | en_HK |
dc.subject | Threshold models | en_HK |
dc.subject | Value-at-risk | en_HK |
dc.title | On some models for value-at-risk | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0747-4938&volume=29&spage=622&epage=641&date=2010&atitle=On+some+models+for+value-at-risk | en_HK |
dc.identifier.email | Yu, PLH: plhyu@hkucc.hku.hk | en_HK |
dc.identifier.email | Li, WK: hrntlwk@hku.hk | en_HK |
dc.identifier.authority | Yu, PLH=rp00835 | en_HK |
dc.identifier.authority | Li, WK=rp00741 | en_HK |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1080/07474938.2010.481972 | en_HK |
dc.identifier.scopus | eid_2-s2.0-77956758299 | en_HK |
dc.identifier.hkuros | 181200 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-77956758299&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 29 | en_HK |
dc.identifier.issue | 5 | en_HK |
dc.identifier.spage | 622 | en_HK |
dc.identifier.epage | 641 | en_HK |
dc.identifier.isi | WOS:000281853600007 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Yu, PLH=7403599794 | en_HK |
dc.identifier.scopusauthorid | Li, WK=14015971200 | en_HK |
dc.identifier.scopusauthorid | Jin, S=35757710200 | en_HK |
dc.identifier.issnl | 0747-4938 | - |