Exploring frequency of price overreactions in the Ukrainian stock market

This study aims to investigate the role of Fintech in predicting the spread of COVID-19 based on consumers’ Fintech perceptions and behavior before and after the outbreak of COVID-19. The study used a questionnaire-based survey distributed in different countries of the world using the LinkedIn platform for this purpose to reach the targeted population. The snowball sampling technique was used. The study targeted consumers with Fintech experience, especially in digital payments services. 507 samples were retrieved. For the analysis, the Structural Equation Modeling (SEM) was used. The study revealed novel results in predicting COVID-19 spread; these three variables (Fintech Behavior before COVID-19, Fintech Behavior after COVID-19, and Fintech Perception after COVID-19) could predict 52.5% of the variance in the dependent variable (COVID-19 Spread) (R² = 0.525, p < 0.05). The findings show that Higher Fintech perception and behavior among Fintech users will help in reducing the spread of COVID-19 by avoiding the use of contact payment methods. Contactless payment methods are the main tools in Fintech that might help in avoiding the probability of COVID-19 spread. Consumers’ Fintech perceptions and behavior are the most influencing factors that could predict the spread of COVID-19 in this study, where digital payments are the main concern. It is recommended that consumers adopt digital payment methods and tools, especially contactless payment methods, to fulfill their financial services. Other researchers are also encouraged to use the same model to predict the spread of this virus in the Fintech context.

The banking industry is one of the major industries in the Vietnamese stock market, so understanding how the industry index reacts to unusual events such as COVID-19’s impact is very important for the development of the Vietnamese stock market. This study examines the response of the banking sector index to three lockdown/blockage announcements to prevent the COVID-19 epidemic in Vietnam in 2020. Three times of lockdown/blockage: On February 13, 2020, blockade of Son Loi commune, Vinh Phuc province; on March 30, 2020, Vietnam announced the nationwide epidemic of COVID-19 and then nationwide lockdown, and on July 28, 2020, blockade in Da Nang. In the first case, the abnormal returns changed the sign around the notification date indicating that the stock price deviated from its fair value, but accumulating abnormal returns CAR (0;3] and CAR (0; 2] are both positive and statistically significant, which means that investors are more secure when the epidemic area is tightly controlled. The nationwide lockdown was the event that had the strongest impact on the stock price when both AR and CAR were negative and statistically significant before and after the date of the event’s announcement. Nationwide lockdown was the event that had the strongest impact on stock prices as both AR and CAR were negative in the days before and days after the event. This result supports the theory of imperfect substitution. Only AR [2] was positive and statistically significant, showing that the blockade event in Da Nang had a slight impact on the banking sector’s stock price.

The government bond (GB) has become the most attractive investment portfolio option, even though many macroeconomic factors affect the bond yield. This paper aims to investigate the determining factor of local currency government bond yield by considering the inflation rate, credit default swap, stock market index, exchange rate, and volatility index. This study used 240 data panel from the Bloomberg stock market in the form of data panel covering Southeast developing countries, namely Indonesia, Thailand, Malaysia, and the Philippines, for five years or sixty months from January 2015 to December 2019. Data analysis used recursive models and multivariate regression techniques using EViews software. The random effect model results revealed that change in the foreign exchange rate and volatility indexes affected, partially and simultaneously, the changes in the stock market index. The result also showed that changes in the stock market index, inflation rate, and credit default swap affected, partially and simultaneously, government bond yield changes. These results suggest that the government bond yield could be managed by controlling volatility index, foreign exchange rate, stock market index, inflation rates, and credit default swaps. This finding could provide an insight into the policymaker and fiscal authority on managing the risk of government bonds under control during high volatility or even making it reasonably lower. This result could contribute to the current research in the field of financial management.

Acknowledgment
It is the author’s pleasure to thank Muhammad Aulia SE MSc CSA® from the Ministry of Finance of Republic Indonesia, for his invaluable contribution to encourage this study and also to share the data required for this paper. He also delivers essential insights into improving the quality of this work. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.