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DC Field | Value | Language |
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dc.contributor.author | Quanrui Song | en_US |
dc.contributor.author | Jianxu Liu | en_US |
dc.contributor.author | Songsak Sriboonchitta | en_US |
dc.date.accessioned | 2019-08-05T04:39:42Z | - |
dc.date.available | 2019-08-05T04:39:42Z | - |
dc.date.issued | 2019-01-01 | en_US |
dc.identifier.issn | 22277390 | en_US |
dc.identifier.other | 2-s2.0-85063904413 | en_US |
dc.identifier.other | 10.3390/math7030274 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85063904413&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/65700 | - |
dc.description.abstract | © 2019 by the authors. Multivariate copulas have been widely used to handle risk in the financial market. This paper aimed to adopt two novel multivariate copulas, Vine copulas and Factor copulas, to measure and compare the financial risks of the emerging economy, developed economy, and global economy. In this paper, we used data from three groups (BRICS, which stands for emerging markets, specifically, those of Brazil, Russia, India, China, and South Africa; G7, which refers to developed countries; and G20, which represents the global market), separated into three periods (pre-crisis, crisis, and post-crisis) and weighed Value at Risk (VaR) and Expected Shortfall (ES) (based on their market capitalization) to compare among three copulas, C-Vine, D-Vine, and Factor copulas. Also, real financial data demonstrated that Factor copulas have stronger stability and perform better than the other two copulas in high-dimensional data. Moreover, we showed that BRICS has the highest risk and G20 has the lowest risk of the three groups. | en_US |
dc.subject | Mathematics | en_US |
dc.title | Risk measurement of stock markets in BRICS, G7, and G20: Vine copulas versus factor copulas | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Mathematics | en_US |
article.volume | 7 | en_US |
article.stream.affiliations | Shandong University of Finance and Economics | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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