Studies of Rank and Tail Dependence Represented by Copula Function
Ji Yanli · Jingji wenti · 2009
To describe joint distribution's characters,the first step is seeing about the dependent structure.The most classic one is the linear correlation coefficient.It is well known that the base of linear correlation coefficient is normal distribution,so there are several limitations when using it.Rank and tail dependence represented by the Copula function are stable,and extreme values can't affect them easily.They don't need the assumption of normal distribution.A simulative example has been given to compute the t-Copula's rank and tail dependence.