Similarity‐Dissimilarity in the Asian Financial Markets Integration: A Four‐Moment Approach to Examining Convergence‐Divergence to Global Financial Market Centroids

This study investigates the evolving integration of 10 major Asian stock markets with key global and regional financial centres, namely, the U.S., China, the E.U., and a constructed Asia centroid. Incorporating all four statistical moments (mean, variance, skewness, and kurtosis), we compute pairwise Euclidean distances to evaluate the degree of similarity in return distributions between Asian markets and each centroid. Our analysis proceeds in three stages. First, we assess the average cross‐sectional proximity between each market and the centroids using a network graph, revealing that, despite geographic closeness, China exhibits the highest average dissimilarity, while the Asia centroid displays the strongest alignment. Second, we explore time trend regressions of these distances to identify convergence or divergence patterns. The findings show that convergence is primarily associated with the risk‐only measure rather than return‐only, return–risk, or four‐moment measures. Importantly, this trend is especially evident in the growing alignment of South‐East Asian markets with China, even though China initially appears the most dissimilar to Asian stock markets. Finally, the efficient frontier analyses across the four identified sub‐periods, namely the GFC (2007–2009), the post‐GFC recovery (2010–2019), the COVID‐19 shock (2020–2022), and the post‐COVID period (2023 onward), highlight how investment efficiency and diversification benefits vary over time. Our findings provide new insights into regional financial interdependencies and provide practical implications for adaptive portfolio strategies.