Abstract

Manuscript type: An empirical analysis of the relationship between country-level governance and share markets in the Asia-Pacific region was carried out using dynamic value at risk (Dynamic VaR), mixed data sample (MIDAS) and exponential generalised autoregressive conditional heteroskedasticity (EGARCH) models. Research question/issue: Is there a relationship between a country’s governance and stock market in terms of the level of returns and share price volatility? We hypothesise that stock returns for countries with higher levels of governance will have lower ex ante expected returns and less volatility than countries with lower levels of governance. Research findings/insights: It is evident from the empirical findings that there is still significant diversity in both corporate-level governance and country-level governance within the Asia-Pacific region. The results from using mixed data sample-autoregressive distributed lag (MIDAS-ADL) model correlation between world governance index (WGI) and the dynamic VaR suggest that the estimators of high frequency slope for India, China and Malaysia are negative. In addition, their t statistics show that the correlation is significant; meanwhile, their goodness of fit is also very high confirming the explanation power of MIDAS-AD model. Consequently, the capital market performances of India, China and Malaysia are negatively related to their corporate-level governance and country-level governance. However, China has a positive correlation between WGI and corporate-level governance and country-level governance. This uncommon phenomenon may be the result of its special political system and the segregation of the capital market and the real economy. Theoretical/academic implications: The linkage between country-level governance and volatility of stocks in Asia-Pacific markets indicates there is scope to reduce stock price volatility through enhanced national governance. Volatility as an indicator of risk reflects market uncertainty in terms of processing information signals to find the equilibrium return risk nexus. Consequently, researchers have to incorporate the data of different frequency into the same equation using robust methods. Practitioner/policy implications: Regulatory frameworks encompassing stock markets will benefit from a more focussed consideration of the way in which governance and risk are correlated. Findings from the generalised autoregressive conditional heteroskedasticity (GARCH) and VaR analysis are that stock market volatility is a suitable proxy for the governance of a country. As country governance indices are annual at best, volatility measures give more timely readings. An increase in volatility suggests there is a decline in national governance, and this has implications for those involved in trade, donor organisations and international lending agencies such as the World Bank.

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