Robust Score and Portmanteau Tests of Volatility Spillover
49 Pages Posted: 12 Feb 2012 Last revised: 14 May 2013
Date Written: April 20, 2013
Abstract
This paper presents a variety of tests of volatility spillover that are robust to heavy tails generated by large errors or GARCH-type feedback. The tests are couched in a general conditional heteroskedasticity framework with idiosyncratic shocks that are only required to have a finite variance if they are independent. We negligibly trim test equations, or components of the equations, and construct heavy tail robust score and portmanteau statistics. We develop the tail-trimmed sample correlation coefficient for robust inference, and prove that its Gaussian limit under the null hypothesis of no spillover has the same standardization irrespective of tail thickness. Further, if spillover occurs within a specified horizon, our test statistics obtain power of one asymptotically. A Monte Carlo study shows our tests provide significant improvements over extant GARCH-based tests of spillover, and we apply the tests to financial returns data.
Keywords: volatility spillover, heavy tails, tail trimming, robust inference
JEL Classification: C13, C20, C22
Suggested Citation: Suggested Citation
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