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

• Main Authors: K. Autchariyapanitkul, S. Sriboonchitta, S. Chanaim
• Format: Journal
• Published: 2018
• Subjects: Mathematics
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84907234273&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/53674
• Institution: Chiang Mai University

© 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.