Volatility Spillovers and Market Integration: A Dynamic Connectedness Analysis of Emerging and Developed Stock Markets (2010–2024)

Abstract

This study investigates the dynamic volatility spillovers and market connectedness between emerging and developed stock markets over the period 2010–2024. Employing the Time-Varying Parameter Vector Autoregressive (TVP-VAR) model combined with the Diebold-Yilmaz connectedness framework, we analyze the magnitude, direction, and time-varying nature of volatility transmission across fifteen major stock market indices. The sample includes eight developed markets (United States, United Kingdom, Germany, France, Japan, Canada, Australia, and Switzerland) and seven emerging markets (China, India, Brazil, Russia, South Africa, Mexico, and Indonesia). Our empirical findings reveal that developed markets, particularly the United States, serve as dominant transmitters of volatility spillovers, while emerging markets predominantly act as net receivers. The total connectedness index exhibits significant time variation, with pronounced spikes during the European sovereign debt crisis, the Chinese stock market turbulence of 2015–2016, and most notably during the COVID-19 pandemic. The results demonstrate that crisis periods substantially intensify cross-market volatility linkages, reducing the benefits of international portfolio diversification precisely when they are most needed. These findings carry significant implications for international investors, portfolio managers, and policymakers seeking to understand systemic risk transmission and develop effective risk management strategies in an increasingly interconnected global financial system.