Efficient frontier of global healthcare portfolios using high dimensions of copula models
© Springer International Publishing Switzerland 2016. This paper aims to find the optimal Global Healthcare Portfolios at different levels of risks and returns to obtain the efficient frontier. The risks are measured by expected shortfall. The dependency of selected stocks in portfolios cannot be ig...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Book Series |
Published: |
2017
|
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84952700783&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42389 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
id |
th-cmuir.6653943832-42389 |
---|---|
record_format |
dspace |
spelling |
th-cmuir.6653943832-423892017-09-28T04:26:52Z Efficient frontier of global healthcare portfolios using high dimensions of copula models Thianpaen N. Chanaim S. Sirisrisakulchai J. Sriboonchitta S. © Springer International Publishing Switzerland 2016. This paper aims to find the optimal Global Healthcare Portfolios at different levels of risks and returns to obtain the efficient frontier. The risks are measured by expected shortfall. The dependency of selected stocks in portfolios cannot be ignored. The high-dimension copula-models are used to capture the dependency parameters of the selected stocks. Five largest market capitalization stocks in the global healthcare sector are selected for this analysis. According to the Akaike Information Criterion (AIC), the empirical results show that t-copula is better fitted between the t- and the Gaussian copulas. Based on the t-copula, the result of this study which is the efficient frontier of the global healthcare portfolios is finally shown in Table 4 for related decision makers. 2017-09-28T04:26:52Z 2017-09-28T04:26:52Z 2016-01-01 Book Series 1860949X 2-s2.0-84952700783 10.1007/978-3-319-27284-9_23 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84952700783&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42389 |
institution |
Chiang Mai University |
building |
Chiang Mai University Library |
country |
Thailand |
collection |
CMU Intellectual Repository |
description |
© Springer International Publishing Switzerland 2016. This paper aims to find the optimal Global Healthcare Portfolios at different levels of risks and returns to obtain the efficient frontier. The risks are measured by expected shortfall. The dependency of selected stocks in portfolios cannot be ignored. The high-dimension copula-models are used to capture the dependency parameters of the selected stocks. Five largest market capitalization stocks in the global healthcare sector are selected for this analysis. According to the Akaike Information Criterion (AIC), the empirical results show that t-copula is better fitted between the t- and the Gaussian copulas. Based on the t-copula, the result of this study which is the efficient frontier of the global healthcare portfolios is finally shown in Table 4 for related decision makers. |
format |
Book Series |
author |
Thianpaen N. Chanaim S. Sirisrisakulchai J. Sriboonchitta S. |
spellingShingle |
Thianpaen N. Chanaim S. Sirisrisakulchai J. Sriboonchitta S. Efficient frontier of global healthcare portfolios using high dimensions of copula models |
author_facet |
Thianpaen N. Chanaim S. Sirisrisakulchai J. Sriboonchitta S. |
author_sort |
Thianpaen N. |
title |
Efficient frontier of global healthcare portfolios using high dimensions of copula models |
title_short |
Efficient frontier of global healthcare portfolios using high dimensions of copula models |
title_full |
Efficient frontier of global healthcare portfolios using high dimensions of copula models |
title_fullStr |
Efficient frontier of global healthcare portfolios using high dimensions of copula models |
title_full_unstemmed |
Efficient frontier of global healthcare portfolios using high dimensions of copula models |
title_sort |
efficient frontier of global healthcare portfolios using high dimensions of copula models |
publishDate |
2017 |
url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84952700783&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42389 |
_version_ |
1681422180131274752 |