— Copula is introduced as a tool for understanding the dependence structure among random variables. Copulas make a link between multivariate joint distributions and univariate marginal distributions, and provide a flexible way to describe nonlinear dependence; copulas therefore have been applied in many fields. Here we deal with a family of generalized Archimedean (GA) copulas. In terms of these GA copulas, we derive the formula for the Kendall’s tau, which is a well known measure of concordance. Applications to the management are discussed.
— Copula, (generalized) Archimedean copula, Kendall’s tau, information management.
N. Ishimura is with the Graduate School of Economics, Hitotsubashi University, Kunitachi, Tokyo 186-8601, Japan (e-mail: email@example.com).
T. Li was with Hitotsubashi University. She is now with the Kokusai Asset Management Co. Ltd., Japan (e-mail: firstname.lastname@example.org).
M. A. Nakamura is with the College of Science and Technology, Nihon University, Kanda-Surugadai, Tokyo 101-8308, Japan (e-mail: email@example.com).
Cite: Naoyuki Ishimura, Ting Li, and Masa Aki Nakamura, " Copulas and the Information Management," International Journal of Information and Electronics Engineering vol. 4, no. 3, pp. 180-183, 2014.