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J. Risk Financial Manag. 2017, 10(4), 19; https://doi.org/10.3390/jrfm10040019

Bivariate Kumaraswamy Models via Modified FGM Copulas: Properties and Applications

Department of Mathematics and Statistics, University of North Carolina, Wilmington, NC 28403, USA
Received: 13 September 2017 / Revised: 15 October 2017 / Accepted: 26 October 2017 / Published: 1 November 2017
(This article belongs to the Special Issue Extreme Values and Financial Risk)
Full-Text   |   PDF [278 KB, uploaded 1 November 2017]

Abstract

A copula is a useful tool for constructing bivariate and/or multivariate distributions. In this article, we consider a new modified class of FGM (Farlie–Gumbel–Morgenstern) bivariate copula for constructing several different bivariate Kumaraswamy type copulas and discuss their structural properties, including dependence structures. It is established that construction of bivariate distributions by this method allows for greater flexibility in the values of Spearman’s correlation coefficient, ρ and Kendall’s τ . View Full-Text
Keywords: bivariate Kumaraswamy distribution; copula based construction; Kendall’s tau; dependence structures bivariate Kumaraswamy distribution; copula based construction; Kendall’s tau; dependence structures
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ghosh, I. Bivariate Kumaraswamy Models via Modified FGM Copulas: Properties and Applications. J. Risk Financial Manag. 2017, 10, 19.

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