Evaluating the performance of the Motley Fool’s Stock Advisor™

This study examined the response of stock prices on the Indonesia Stock Exchange (IDX) to COVID-19 using an event study approach and the GARCH model. The research sample is the closing price of the Composite Stock Price Index (JCI) and companies that are members of LQ-45 in the 40-day period before the COVID-19 incident, 1 day during the COVID-19 incident (March 2, 2020) and 10 days after, January 6, 2020 – March 16, 2020. Empirical findings prove that abnormal returns react negatively to COVID-19, JCI volatility fluctuates widely during the COVID-19 event, and the GARCH(1,2) model can be used to assess volatility and predict stock abnormal returns in IDX in market conditions infected with COVID-19. The practical implication of the study’s findings for investors is that the COVID-19 event caused stock price volatility, which affects abnormal returns. Therefore, to face the conditions of uncertainty and increased volatility in the future, several lines of risk management are needed in managing a stock portfolio. In addition, it also opens up opportunities for speculators to profit in an inefficient market environment. This study is based on the empirical literature currently being developed to investigate the phenomenon of stock price volatility behavior during COVID-19 on the IDX. The GARCH model used proves that during the COVID-19 pandemic, stock price volatility increases and leads to a decrease in abnormal returns. The empirical findings also validate the efficient market hypothesis theory related to the study of events and the theory of financial behavior related to uncertainty.

FinTech innovations are one of strategic decisions to increase the profitability of a company. This study determines the level of profitability of companies before and after the emergence of FinTech products. The authors focused on companies that have launched FinTech products and published their financial reports. The study sample consisted of 17 FinTech products from 16 companies in Indonesia. The limited number of the sample was caused by not all of them having published its financial reports, while we have checked 157 FinTech companies. An event study approach using paired sample T-test is utilized. The period used in this study is four years, covering two years before and two years after the company launched FinTech products. Data were obtained from IDX, FinTech.id, and company web-pages. The results clearly showed that there was a significant influence on return on assets (ROA), but no significant difference in return on equity (ROE). This finding gives more contribution to the FinTech industry about the company’s profitability impact of launching FinTech product.

We re-examine the abnormal returns (ARs) around merger announcements using a large sample of 8,945 announcements. We estimate the ARs using the Carhart (1997) four-factor model under the standard ordinary least square (OLS) method and the Glosten et al.’s (1993) asymmetric GARCH specification (hereafter, GJR-GARCH). Under the OLS method, acquirers do not generate significant cumulative ARs (CARs) in line with prior work. Our new results, however, show that under the GJR-GARCH estimation, acquirers generate positive and significant cumulative CARs. We attribute the gains to the use of the GJR-GARCH estimation method, as the GJR-GARCH method is more effective in capturing conditional volatility and asymmetry in the excess returns.