This study investigates the roles of climate policy uncertainty, oil price shocks, and global macro-financial factors in shaping stock-market volatility in Thailand, an emerging economy undergoing an energy transition and increasing financial integration. Using monthly data from January 2000 to September 2025, we estimate a GARCH(1,1) model with exogenous regressors to capture conditional heteroscedasticity and employ support vector regression (SVR) to assess nonlinear out-of-sample predictability. The results indicate that oil-price changes, exchange-rate movements, and global-equity returns exert significant contemporaneous effects on Thai stock returns. In contrast, climate- and policy-related uncertainty measures appear to play a more indirect role within broader volatility dynamics rather than serving as primary return drivers. Volatility persistence is high but mean-reverting, suggesting sustained yet stabilizing adjustment processes in a semi-integrated emerging market. Out-of-sample evidence shows that SVR outperforms both GARCH and random-walk benchmarks, indicating the presence of partial predictability under structured uncertainty. These findings contribute to the understanding of financial stability under transition-related risks and highlight the importance of consistent policy communication in emerging markets.
Huỳnh et al. (Sun,) studied this question.