Eva Nur
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Do COVID-19 containment policies influence equity market returns? Evidence from the ASEAN-5
Investment Management and Financial Innovations Volume 23, 2026 Issue #2 pp. 442–459
Views: 16 Downloads: 2 TO CITE АНОТАЦІЯType of the article: Research Article
Abstract
This study investigates the short- and long-term effects of the COVID-19 pandemic on ASEAN-5 stock markets, Malaysia, Indonesia, Singapore, Thailand, and the Philippines, emphasizing differences between cyclical and non-cyclical sectors. It aims to evaluate how effectively these emerging markets are handling pandemic-related information in a context of extreme uncertainty. The study employs the event study and Buy-and-Hold Abnormal Return (BHAR) methodologies for the year 2020. The finding indicates asymmetric market responses across the ASEAN-5. In the short term, Malaysia (–0.56%), Indonesia (–8.35%), and Singapore (–0.42%) experienced significant declines in cumulative abnormal returns (CAR) (–1,1). Long-term results for 1 to 6 months show gradual recovery in Malaysia (6.97%), Indonesia (5.13%), and Singapore (7.65%). Sectoral analysis reveals that Malaysia’s financial sector (FIN) posted CAR of three days (−1.68%) (p < 0.01) and five days (−3.18%) (p < 0.10). Next comes Indonesia’s cyclical sector, the transportation sector’s three-day (−9.40%) and five-day (21.91%) CAR (both p < 0.01). For Singapore’s mineral resources (MR), the two-day (−1.74%) and seven-day (−2.91%) CARs are statistically significant at least at 10%. In the Philippines, the sectoral reaction was −0.94% to −2.44% over two and seven days for the financial (FIN) sector; in Thailand, the financial (FIN) and utilities (UTI) sectors had CAR of −2.26% over three days and −4.58% over three days, respectively. These findings support the semi-strong form of market efficiency, indicating temporary deviations in behavior. The paper provides a comprehensive review of market efficiency in systemic crises and new insights into sector resilience and policy-driven economic recovery in developing countries.Acknowledgment
This paper used Generative Artificial Intelligence (AI) such as ChatGPT and Co-Pilot to improve the language and the core idea.

