Guglielmo Maria Caporale

This paper is a comprehensive investigation of calendar anomalies in the Ukrainian stock market. It employs various statistical techniques (average analysis, Student’s t-test, ANOVA, the Kruskal-Wallis test, and regression analysis with dummy variables) and a trading simulation approach to test for the presence of the following anomalies: day-of-the-week effect; turn-of-the-month effect; turn-of-the-year effect; month-of-the-year effect; January effect; holiday effect; Halloween effect. The results suggest that in general calendar anomalies are not present in the Ukrainian stock market, but there are a few exceptions, i.e. the turn-of-the-year and Halloween effect for the PFTS index, and the month-of-the-year effect for UX futures. However, the trading simulation analysis shows that only trading strategies based on the turn-of-the-year effect for the PFTS index and the month-of-the-year effect for the UX futures can generate exploitable profit opportunities that can be interpreted as evidence against market efficiency.

This paper examines reactions in the Ukrainian stock market to force majeure events, which are divided into four groups: economic force majeure, social force majeure, terrorist acts, natural and technological disasters. More specifically, using daily data for the main Ukrainian stock market index (namely PFTS) over the period from January 1, to December 31, 2018 this study investigates whether or not force majeure events create (temporary) inefficiencies and there exist profitable trading strategies based on exploiting them. For this purpose, cumulative abnormal returns and trading simulation approaches are used in addition to Student’s t-tests. The results suggest that the Ukrainian stock market absorbs new information rather fast. Negative returns in most cases are observed only on the day of the event. The only exception is technological disasters, the market needing up to ten days to react fully in this case. Despite the presence of a detectable pattern in price behavior after force majeure events (namely, a price decrease on the day of the event) no profitable trading strategies based on it are found as their outcomes do not differ from those generated by random trading.