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dc.titleTVICA - Time varying independent component analysis and its application to financial data
dc.contributor.authorChen, R.-B.
dc.contributor.authorChen, Y.
dc.contributor.authorHärdle, W.K.
dc.identifier.citationChen, R.-B., Chen, Y., Härdle, W.K. (2014-06). TVICA - Time varying independent component analysis and its application to financial data. Computational Statistics and Data Analysis 74 : 95-109. ScholarBank@NUS Repository.
dc.description.abstractA new method of ICA, TVICA, is proposed. Compared to the conventional ICA, the TVICA method allows the mixing matrix to be time dependent. Estimation is conducted under local homogeneity that assumes at any particular time point, there exists an interval over which the mixing matrix can be well approximated as constant. A sequential log likelihood-ratio testing procedure is used to automatically identify such local intervals. Numerical analysis demonstrates that TVICA provides good performance in homogeneous situations and does improve accuracy in nonstationary settings with possible structural change. In real data analysis with application to risk management, the TVICA confirms a superior performance when compared to several alternatives, including ICA, PCA and DCC-based models. © 2014 Elsevier B.V. All rights reserved.
dc.subjectAdaptive methods
dc.subjectLocal homogeneity
dc.subjectPortfolio risk analysis
dc.subjectSequential testing
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.sourcetitleComputational Statistics and Data Analysis
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