Some alternative bivariate Kumaraswamy-type distributions via copula with application in risk management

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.

KEYWORDS:

• Bivariate Kumaraswamy distribution
• bivariate Kumaraswamy-type copula
• dependence structure
• risk management

AMS SUBJECT CLASSIFICATION:

• 60E
• 62F