This study aims to analyze the impact of the COVID-19 pandemic on Indonesia’s stock market performance. Considering the characteristics of daily stock return data that shows the characteristics of volatility clustering, the analytical method used is to develop a heteroscedastic model specification whose parameters are estimated using the maximum likelihood method. Based on data from March 2020 to January 2021, this study finds that the Exponential-GARCH asymmetric model is the best model compared to the Standard-GARCH symmetric model or the asymmetric Threshold-GARCH model. The inference analysis conducted on the Exponential-GARCH asymmetric model in this study shows that the stock market's performance that is significantly affected by this pandemic is the volatility of its returns. Stock price volatility is one of the important variables in stock market performance. This study produces empirical findings that government policies on social restrictions contribute significantly to suppressing stock market volatility. As for government policies in mitigating the risk of the spread of the epidemic, in this study, it is measured through a stringency index. This index was released by the Oxford COVID-19 Government Response Tracker (OxCGRT) which monitors the government's response to the coronavirus in 160 countries and is a parameter that evaluates the policies taken by a country's government based on nine metrics. This index does not measure the effectiveness of a country's government response, but only the level of tightness. However, the results of the tests carried out in this study did not find a significant impact of pandemic indicators, the number of cases, and the number of daily deaths related to COVID-19 on stock returns.
The impact of COVID-19 on stock market performance in Africa: A Bayesian structural time series approach
