Tail Risk Dynamics in Stock Returns: Links to the Macroeconomy and Global Markets Connectedness

Abstract

We propose a new time-varying peaks over threshold model to study tail risk dynamics in equity markets: the laws of motion for the parameters are defined through the score-based approach. We apply the model to daily returns from U.S. size-sorted decile stock portfolios and show that large firms' tail risk increases during recessions more than small firms' tail risk. Our results are consistent with the granular hypothesis of aggregate fluctuations, and we quantify the impact of large firms' tail risk shocks on the economy. A measure of tail connectedness is proposed: evidence from international equity markets shows that tail connectedness increases during periods of turmoil. This paper was accepted by Lauren Cohen, finance.