Some alternative bivariate Kumaraswamy-type distributions via copula with application in risk management. (1st October 2016)

• Record Type: Journal Article
• Authors: Ghosh, Indranil; Ray, Samik
• Is Part Of: Journal of statistical theory and practice. Volume 10:Number 4(2016)
• Page Start: 693
• Page End: 706
• Publication Date: 2016-10-01
• Subjects: Bivariate Kumaraswamy distribution -- bivariate Kumaraswamy-type copula -- dependence structure -- risk management; 60E -- 62F; 519.505
• DOI: 10.1080/15598608.2016.1215943
• Languages: English
• ISSNs: 1559-8608

Abstract

ABSTRACT: In this article we discuss various strategies for constructing bivariate Kumaraswamy distributions via the copula approach. The copula methods and construction studied here are different from those briefly discussed in Arnold and Ghosh (2016). In this article, bivariate normal copula, AMH (Ali–Mikhail–Haq), and Marshall–Olkin copula generators were assumed to construct bivariate Kumaraswamy models. Additionally, we consider here a few different types of copula generators, which subsume Clayton copula type generators. Various structural properties of the derived copulas including tail dependence, correlation coefficient, and others are discussed.