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Conference Paper: Volatility modelling of multivariate financial time series by using ICA-GARCH models

TitleVolatility modelling of multivariate financial time series by using ICA-GARCH models
Authors
KeywordsFinancial Engineering
GARCH
ICA
Multivariate Time Series
Volatility
Issue Date2005
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
Intelligent Data Engineering and Automated Learning – IDEAL 2005, Lecture Notes in Computer Science, Volume 3578, p. 571-579 How to Cite?
AbstractVolatility modelling of asset returns is an important aspect for many financial applications, e.g., option pricing and risk management. GARCH models are usually used to model the volatility processes of financial time series. However, multivariate GARCH modelling of volatilities is still a challenge due to the complexity of parameters estimation. To solve this problem, we suggest using Independent Component Analysis (ICA) for transforming the multivariate time series into statistically independent time series. Then, we propose the ICA-GARCH model which is computationally efficient to estimate the volatilities. The experimental results show that this method is more effective to model multivariate time series than existing methods, e.g., PCA-GARCH. © Springer-Verlag Berlin Heidelberg 2005.
Persistent Identifierhttp://hdl.handle.net/10722/110229
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorWu, EHCen_HK
dc.contributor.authorYu, PLHen_HK
dc.date.accessioned2010-09-26T01:56:47Z-
dc.date.available2010-09-26T01:56:47Z-
dc.date.issued2005en_HK
dc.identifier.citationIntelligent Data Engineering and Automated Learning – IDEAL 2005, Lecture Notes in Computer Science, Volume 3578, p. 571-579en_HK
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/110229-
dc.description.abstractVolatility modelling of asset returns is an important aspect for many financial applications, e.g., option pricing and risk management. GARCH models are usually used to model the volatility processes of financial time series. However, multivariate GARCH modelling of volatilities is still a challenge due to the complexity of parameters estimation. To solve this problem, we suggest using Independent Component Analysis (ICA) for transforming the multivariate time series into statistically independent time series. Then, we propose the ICA-GARCH model which is computationally efficient to estimate the volatilities. The experimental results show that this method is more effective to model multivariate time series than existing methods, e.g., PCA-GARCH. © Springer-Verlag Berlin Heidelberg 2005.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Scienceen_HK
dc.subjectFinancial Engineeringen_HK
dc.subjectGARCHen_HK
dc.subjectICAen_HK
dc.subjectMultivariate Time Seriesen_HK
dc.subjectVolatilityen_HK
dc.titleVolatility modelling of multivariate financial time series by using ICA-GARCH modelsen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailYu, PLH: plhyu@hkucc.hku.hken_HK
dc.identifier.authorityYu, PLH=rp00835en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-26444479340en_HK
dc.identifier.hkuros133495en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-26444479340&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume3578en_HK
dc.identifier.spage571en_HK
dc.identifier.epage579en_HK
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridWu, EHC=25958488900en_HK
dc.identifier.scopusauthoridYu, PLH=7403599794en_HK

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