Journal article
Multivariate dependence risk and portfolio optimization: An application to mining stock portfolios
Resources policy, v 46(2), pp 1-11
Dec 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This study proposes an integrated framework to model and estimate relatively large dependence matrices using pair vine copulas and minimum risk optimal portfolios with respect to five risk measures within the context of the global financial crisis. We apply this methodology to two 20-asset mining (gold and iron ore-nickel) sector portfolios from the Australian Securities Exchange. The pair vine copulas prove to be powerful tools for the modeling of changing dependence risk under three different period scenarios combined with the optimization of portfolios that have complex patterns of dependence. The portfolio optimization results converge, on average, in some stocks.
1.Integrated framework to model and estimate relatively large dependence matrices2.Pair vine copulas, min-risk optimal portfolios and 5 risk measures are used3.Methodology is applied to two 20-asset gold and iron ore-nickel sector portfolios4.Dependence risk is modeled under 3 scenarios within the global financial crisis5.Portfolio optimization results converge on average to particular stocks
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Details
- Title
- Multivariate dependence risk and portfolio optimization: An application to mining stock portfolios
- Creators
- Stelios Bekiros - European University InstituteJose Arreola Hernandez - Edith Cowan UniversityShawkat Hammoudeh - Drexel UniversityDuc Khuong Nguyen - IPAG Business School
- Publication Details
- Resources policy, v 46(2), pp 1-11
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Economics (School of Economics)
- Web of Science ID
- WOS:000366225600001
- Scopus ID
- 2-s2.0-84938680172
- Other Identifier
- 991019167866404721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Environmental Studies