The stock-cryptocurrency correlation in the Asean +3 region: the role of investor attention and herding

The ASEAN+3 region, particularly Indonesia and the Philippines, has exhibited some of the highest levels of international cryptocurrency adoption. However, limited research has examined the influence of behavioral factors on the integration of cryptocurrencies, including Bitcoin, into conventional financial markets such as stock markets. This study investigates the behavioral drivers underlying the correlation between stock markets and cryptocurrencies in the ASEAN+3 economies, comprising Singapore, Indonesia, Thailand, Malaysia, the Philippines, Japan, China, and South Korea. Panel autoregressive distributed lag (ARDL) and dynamic conditional correlation multivariate GARCH (DCC-MGARCH) models were applied to an extensive dataset spanning from 2014 to 2024 to capture both long-term and short term trends, using EViews and R for analysis. The results indicate that heightened international market uncertainty and increased investor attention significantly strengthen the long-term correlation between stock and cryptocurrency markets, with herding behavior further reinforcing this relationship. In contrast, greater investor attention weakens the short-term correlation, suggesting speculative divergence, although herding behavior temporarily enhances the linkage during such periods. These findings suggest that emotionally driven, retail-dominated trading behaviors have a stronger influence in the ASEAN+3 region compared to more developed markets, such as South Korea, Japan, and Singapore. This study contributes to the literature by elucidating the role of domestic behavioral dynamics in shaping stock-cryptocurrency interdependencies and by integrating modern portfolio theory with behavioral finance perspectives. Policymakers should leverage these findings to improve existing regulatory frameworks and more effectively protect retail investors, who may be the most vulnerable group amid the rapid growth of cryptocurrency transactions.