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Multivariate Levy Processes for Financial Returns

dc.contributor.advisorMadan, Dilip Ben_US
dc.contributor.authorYen, Ju-Yien_US
dc.description.abstractWe apply a signal processing technique known as independent component analysis (ICA) to multivariate financial time series. The main idea of ICA is to decompose the observed time series into statistically independent components (ICs). We further assume that the ICs follow the variance gamma (VG) process. The VG process is evaluated by Brownian motion with drift at a random time given by a gamma process. We build a multivariate VG portfolio model and analyze empirical results of the investment.en_US
dc.format.extent642873 bytes
dc.titleMultivariate Levy Processes for Financial Returnsen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentApplied Mathematics and Scientific Computationen_US
dc.subject.pqcontrolledEconomics, Financeen_US

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