Institutional Learning and Volatility Transmission in ASEAN Equity Markets: A Network-Integrated Regime-Dependent Approach

TL;DR

This study models how institutional learning and regional spillovers influence volatility in ASEAN equity markets, introducing dynamic frameworks that improve forecasting and reveal the importance of institutional and network effects.

Contribution

It develops a novel dynamic volatility model incorporating institutional response and network interactions, advancing understanding of regional market spillovers and volatility behavior.

Findings

Institutional learning increases short-term shock sensitivity.

Network interactions enhance tail risk modeling and short-term forecasts.

Spillovers are driven by regional common factors, not just correlation structures.

Abstract

This paper investigates how institutional learning and regional spillovers shape volatility dynamics in ASEAN equity markets. Using daily data for Indonesia, Malaysia, the Philippines, and Thailand from 2010 to 2024, we construct a high-frequency institutional learning index via a MIDAS-EPU approach. Unlike existing studies that treat institutional quality as a static background characteristic, this paper models institutions as a dynamic mechanism that reacts to policy shocks, information pressure, and crisis events. Building on this perspective, we introduce two new volatility frameworks: the Institutional Response Dynamics Model (IRDM), which embeds crisis memory, policy shocks, and information flows; and the Network-Integrated IRDM (N-IRDM), which incorporates dynamic-correlation and institutional-similarity networks to capture cross-market transmission. Empirical results show that institutional learning amplifies short-run sensitivity to shocks yet accelerates post-crisis normalization. Crisis-memory terms explain prolonged volatility clustering, while network interactions improve tail behavior and short-horizon forecasts. Robustness checks using placebo and lagged networks indicate that spillovers reflect a strong regional common factor rather than dependence on specific correlation topologies. Diebold-Mariano and ENCNEW tests confirm that the N-IRDM significantly outperforms baseline GARCH benchmarks. The findings highlight a dual role of institutions and offer policy insights on transparency enhancement, macroprudential communication, and coordinated regional governance.