Return spillovers around the globe: A network approach

TL;DR

This paper uses a network approach to analyze global stock market spillovers, revealing how market characteristics, temporal proximity, and existing connections influence return spillovers across countries.

Contribution

It introduces a novel network-based methodology to study international stock return spillovers, incorporating temporal proximity and market development factors.

Findings

Market volatility and size increase spillovers

Foreign exchange volatility decreases spillovers

Temporal proximity enhances spillover probability

Abstract

Using a rolling windows analysis of filtered and aligned stock index returns from 40 countries during the period 2006-2014, we construct Granger causality networks and investigate the ensuing structure of the relationships by studying network properties and fitting spatial probit models. We provide evidence that stock market volatility and market size increases, while foreign exchange volatility decreases the probability of return spillover from a given market. We also show that market development and returns on the foreign exchange market and stock market also matter, but they exhibit significant time-varying behaviour with alternating effects. These results suggest that higher market integration periods are alternated with periods where investors appear to be chasing returns. Despite the significance of market characteristics and market conditions, what in reality matters for information propagation is the temporal distance between closing hours, i.e. the temporal proximity effect. This implies that choosing markets which trade in similar hours bears additional costs to investors, as the probability of return spillovers increases. The same effect was observed with regard to the temporal distance to the US market. Finally, we confirm the existence of the preferential attachment effect, i.e. the probability of a given market to propagate return spillovers to a new market depends endogenously and positively on the existing number of return spillovers from that market.