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DC Field | Value | Language |
---|---|---|
dc.contributor.author | K. Autchariyapanitkul | en_US |
dc.contributor.author | S. Sriboonchitta | en_US |
dc.contributor.author | S. Chanaim | en_US |
dc.date.accessioned | 2018-09-04T09:55:12Z | - |
dc.date.available | 2018-09-04T09:55:12Z | - |
dc.date.issued | 2014-01-01 | en_US |
dc.identifier.issn | 16860209 | en_US |
dc.identifier.other | 2-s2.0-84907234273 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84907234273&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/53674 | - |
dc.description.abstract | © 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. | en_US |
dc.subject | Mathematics | en_US |
dc.title | Portfolio optimization of stock returns in high-dimensions: A copula-based approach | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Thai Journal of Mathematics | en_US |
article.volume | 2014 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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