Institutional learning and volatility transmission in ASEAN equity markets: A network-integrated regime-dependent approach

Most existing studies on emerging-market volatility treat institutional quality as a low-frequency, static background variable, leaving them unable to characterize how institutions adjust in real time to crises, policy signals, and information shocks, or how such adjustments shape cross-market volatility transmission. This paper constructs a MIDAS-based high-frequency institutional learning index derived from economic policy uncertainty (EPU) and introduces two new volatility modeling frameworks: the Institutional Response Dynamics Model (IRDM), which captures the short-run institutional reaction mechanism, and the Network-Integrated IRDM (N-IRDM), which describes the synchronous propagation of institutional responses across markets. Using daily data for Indonesia, Malaysia, the Philippines, and Thailand from 2010–2024, our empirical results show that institutional learning amplifies the immediate volatility response to shocks but subsequently accelerates volatility normalization; that crisis-memory terms exhibit strong persistence; and that network mechanisms significantly improve tail-fit accuracy and short-term forecasting, especially during multi-country crisis episodes. Placebo-network and lagged-network tests further reveal that cross-market institutional spillovers primarily reflect regional common-factor synchronicity rather than dependence on any specific correlation structure. Based on this evidence, we conclude that (i) enhancing transparency and policy-guidance consistency can mitigate the short-run amplification induced by institutional learning, (ii) improving crisis-related information disclosure can weaken the prolonged volatility associated with crisis memory, (iii) strengthening regional regulatory coordination can dampen the synchronous amplification of institutional reactions, and (iv) systematic monitoring of institution- and information-based common factors can help identify early stages of region-wide risk escalation.