Tail connectedness: Measuring the volatility connectedness network of equity markets during crises

Abstract

This paper studies the global volatility connectedness network among 16 stock markets under different market conditions. We construct measures of tail connectedness following Ando et al. (2022) by introducing quantile regression into the classic Diebold–Yilmaz network model. We demonstrate the advantages of using tail connectedness for measuring extreme systemic risk, and examine the dynamic evolution of volatility connectedness from 2005 to 2021 at different quantiles. Our empirical results suggest that when the market is calm, the strength of volatility connectedness is determined by the closeness of economic and trade ties. Although (North) American and European stock markets tend to act as net risk providers during crises, Asian markets have become increasingly influential in the past two decades. We also find that the spillover of extreme risks is predominantly unidirectional, with either the U.S. or China sitting at the center of the spillover network and transmitting risks to the regional centers and peripheral markets.