Portfolio optimization of stock returns in high-dimensions: A copula-based approach

© 2014 by the Mathematical Association of Thailand. All rights reserved. We used the multivariate t copula, which can capture the tail dependence to modeling the dependence structure of the risk in portfolio analysis. Multivariate t copula based on GARCH model was used to explain portfolio risk stru...

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Bibliographic Details
Main Authors: K. Autchariyapanitkul, S. Sriboonchitta, S. Chanaim
Format: Journal
Published: 2018
Subjects:
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84907234273&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/53674
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Institution: Chiang Mai University
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Summary:© 2014 by the Mathematical Association of Thailand. All rights reserved. We used the multivariate t copula, which can capture the tail dependence to modeling the dependence structure of the risk in portfolio analysis. Multivariate t copula based on GARCH model was used to explain portfolio risk structure for high-dimensional asset allocation issue. With this method we used the Monte Carlo simulation and the results of multivariate t copula to estimate the expected shortfall of the portfolio. Finally, we obtained the optimal weighted for conditional Value-at-Risk (CVaR) model with the assumption of multivariate distribution to illustrate the potential model risk among portfolios returns.