TailCoR

TL;DR

TailCoR is a new metric that measures and separates linear and nonlinear tail dependencies between variables, useful for analyzing extreme co-movements in economic and financial crises.

Contribution

It introduces TailCoR, a dimension-free, efficient metric based on tail inter quantile range that disentangles linear and nonlinear dependencies without requiring optimization.

Findings

Performs well in small samples

Effectively separates linear and nonlinear tail dependencies

Applicable to economic and financial crisis analysis

Abstract

Economic and financial crises are characterised by unusually large events. These tail events co-move because of linear and/or nonlinear dependencies. We introduce TailCoR, a metric that combines (and disentangles) these linear and non-linear dependencies. TailCoR between two variables is based on the tail inter quantile range of a simple projection. It is dimension-free, it performs well in small samples, and no optimisations are needed.