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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th-cmuir.6653943832-453082018-01-24T06:08:17Z Portfolio optimization of stock returns in high-dimensions: A copula-based approach K. Autchariyapanitkul S. Sriboonchitta S. Chanaim © 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. 2018-01-24T06:08:17Z 2018-01-24T06:08:17Z 2014-01-01 Journal 16860209 2-s2.0-84907234273 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84907234273&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/45308 |
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© 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. |
| format |
Journal |
| author |
K. Autchariyapanitkul S. Sriboonchitta S. Chanaim |
| spellingShingle |
K. Autchariyapanitkul S. Sriboonchitta S. Chanaim Portfolio optimization of stock returns in high-dimensions: A copula-based approach |
| author_facet |
K. Autchariyapanitkul S. Sriboonchitta S. Chanaim |
| author_sort |
K. Autchariyapanitkul |
| title |
Portfolio optimization of stock returns in high-dimensions: A copula-based approach |
| title_short |
Portfolio optimization of stock returns in high-dimensions: A copula-based approach |
| title_full |
Portfolio optimization of stock returns in high-dimensions: A copula-based approach |
| title_fullStr |
Portfolio optimization of stock returns in high-dimensions: A copula-based approach |
| title_full_unstemmed |
Portfolio optimization of stock returns in high-dimensions: A copula-based approach |
| title_sort |
portfolio optimization of stock returns in high-dimensions: a copula-based approach |
| publishDate |
2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84907234273&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/45308 |
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