TailCoR
Sla{\dj}ana Babi\'c, Christophe Ley, Lorenzo Ricci, David, Veredas

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.
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Monetary Policy and Economic Impact · Financial Risk and Volatility Modeling
