Volatility spillover of cross-border fund flow and the geopolitical risk channels

Abstract

This study investigates cross-border risk spillover led by fund flow volatility. With a focus on global and country-specific geopolitical risk (GPR), we explore vulnerability channels where volatility is transmitted and propagated based on the equity fund flow data of G20 countries. Following a data-driven methodology, we quantify long-term systemic risk spillovers for each country using the PageRank algorithm applied to a volatility network, capturing the intensity of directional, pairwise risk spillovers. Traditional measures of systemic risk often focus on direct pairwise relationships, leaving indirect and multi-step spillovers unquantified. To address this, we adopt a computational network approach, constructing a directed volatility spillover network from G20 fund flow data. PageRank, adapted from graph-based machine learning, captures both direct and indirect risk exposures by modeling risk transmission within the network as a Markov process, providing a data-driven measure of long-term systemic vulnerability for each country. We then analyze these network-derived risk measures using panel regressions with global and country-specific GPR indices, along with recognized push and pull factors, to explore how countries respond differently to geopolitical uncertainties. Our findings reveal cyclic patterns in fund flow dependence, with smaller emerging markets, such as Indonesia, Argentina, Saudi Arabia, and South Africa, showing heightened vulnerability during turmoil. Country-specific GPR emerges as a potent pull factor, especially for oil-exporting economies, while geographic location serves as a primary channel of spillover. In periods of global tension, Latin American emerging markets and the Asia-Pacific region display a “safe-haven” role, contrasting with higher exposure in North America, the Middle East, and Africa. This study demonstrates the potential of computational network methods to advance systemic risk modeling in finance, offering a scalable, data-driven framework for understanding how geopolitical risk interacts with cross-border capital flows.