TailCoR Lorenzo RICCI

We introduce TailCoR, a new measure for tail correlation that is a function of linear and non–linear contributions, the latter characterized by the tails. TailCoR can be exploited in a number of financial applications, such as portfolio selection where the investor faces risks of linear and tail nature –a case that we cover in detail. Moreover, TailCoR has the following advantages: i) it is exact for any probability level as it is not based on tail asymptotic arguments (contrary to tail dependence coefficients), ii) it is distribution free, and iii) it is simple and no optimizations are needed. Monte Carlo simulations and calibrations reveal its goodness in finite samples. An empirical illustration to a panel of European sovereign bonds shows that prior to 2009 linear correlations were in the vicinity of one and non–linear correlations were inexistent. Since the beginning of the crisis the linear correlations have decreased sharply and non–linear correlations appeared and increased significantly in 2010–2011.