Institutional development and stock price synchronicity: A comparative study on the ASEAN-5 region
Efficient Market Hypothesis (EMH) posits that firms in efficient markets can make optimal investment decisions as stock prices reflect information. However, information asymmetries exist between firms and investors. Traditional theory suggest this is due to firm-level decision, while more contempora...
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| Main Authors: | , , , |
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| Format: | text |
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Animo Repository
2021
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/9466 |
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| Institution: | De La Salle University |
| Summary: | Efficient Market Hypothesis (EMH) posits that firms in efficient markets can make optimal investment decisions as stock prices reflect information. However, information asymmetries exist between firms and investors. Traditional theory suggest this is due to firm-level decision, while more contemporary literature suggest that institutional factors may shape corporates’ decision to be disclose information, and thus lead to more informative stock prices. This study aim to provide evidence on the influence of country-level institutional development on firms’ degree of corporate transparency as revealed by their stock price synchronicity. We used panel regression analysis on 420 observations from publicly listed firms culled from Indonesia, Malaysia, Philippines, Singapore, and Thailand from 2013 to 2017. We find that Rule of Law, Voice and Accountability, and Regulatory Quality positively influence the stock price informativeness in Indonesia, Malaysia, the Philippines, and Thailand. Interestingly, we were able to show that Government Effectiveness negatively influences stock price informativeness in Singapore. Finally, our study revealed that Political Stability and Control of Corruption also influence stock price informativeness, but only in Indonesia, Malaysia, Singapore, and Thailand. We recommend future researchers to disaggregate institutional development measures to avoid collinearity. We also recommend researchers to explore this relationship when using clustered industry-level data as some institutional standards and rules are set separately for certain industries. |
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