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Title: Copulas based seemingly unrelated quantile regression
Authors: Roengchai Tansuchat
Paravee Maneejuk
Woraphon Yamaka
Songsak Sriboonchitta
Keywords: Physics and Astronomy
Issue Date: 26-Jul-2018
Abstract: © Published under licence by IOP Publishing Ltd. We propose a multivariate copulas based seemingly unrelated quantile regression. We add the multivariate copula density function into the likelihood to relax the strong assumption of multivariate normal distribution of the conventional model. The simulation study is conducted to evaluate the performance of our proposed model. Moreover, we apply our proposed model to the Fama-French equation in order to investigate the systematic risk in the three major stocks in NASDAQ market. The results of this study suggest that our proposed model provides a particularly good description of these stock prices at every quantile level.
ISSN: 17426596
Appears in Collections:CMUL: Journal Articles

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