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...

Full description

Saved in:
Bibliographic Details
Main Authors: Thianpaen N., Chanaim S., Sirisrisakulchai J., Sriboonchitta S.
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