Multivariate dependence risk and portfolio optimization: An application to mining stock portfolios

被引:40
|
作者
Bekiros, Stelios [1 ,2 ]
Hernandez, Jose Arreola [3 ]
Hammoudeh, Shawkat [2 ,4 ]
Duc Khuong Nguyen [2 ]
机构
[1] European Univ Inst, Dept Econ, I-50133 Florence, Italy
[2] IPAG Business Sch, IPAG Lab, F-75006 Paris, France
[3] Edith Cowan Univ, Sch Business, Joondalup, WA 6027, Australia
[4] Drexel Univ, LeBow Coll Business, Philadelphia, PA 19104 USA
关键词
Mining stocks; Vine copulas; Risk measures; Tail dependence; Portfolio optimization; VINE COPULAS; LIQUIDITY; DECOMPOSITION; MANAGEMENT; VARIANCE; THEOREM; MODEL;
D O I
10.1016/j.resourpol.2015.07.003
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1 / 11
页数:11
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