Equity market anomalies in major European economies

This paper analyzes price gaps in the Ukrainian stock market for the case of UX index over the period 2009–2018. Using different statistical tests (Student’s t-tests, ANOVA, Mann-Whitney test) and regression analysis with dummy variables, as well as modified cumulative approach and trading simulation, the authors test a number of hypotheses searching for price patterns and abnormal market behavior related to price gaps: there is seasonality in price gaps (H1); price gaps generate statistical anomalies in the Ukrainian stock market (H2); upward gaps generate price patterns in the Ukrainian stock market (H3) and downward gaps generate price patterns in the Ukrainian stock market (H4). Overall results are consistent with the Efficient Market Hypothesis: there is no seasonality in price gaps and in most cases there is no evidences of price patterns or abnormal price behavior after the gaps in the Ukrainian stock market. Nevertheless, the authors find very strong and convincing evidences in favor of momentum effect on the days of negative gaps. These observations are confirmed by trading simulations: trading strategy based on detected price pattern generates profits and demonstrates overall efficiency, which is against the market efficiency. These results can be interesting both for academicians (further evidences against market efficiency) and practitioners (real and effective trading strategy to generate profits in the Ukrainian market market).

The Saudi Arabia Stock Exchange (Tadawul) is one of the biggest emerging Stock Exchanges in the Middle East region. Therefore, this research aims to apply Fama and French (2015) 5-factor model on Tadawul, and compares it with the Fama and French 3-factor model and CAPM to check the applicability of the models in Tadawul and the identity of the factors that can affect stock returns. Furthermore, the Generalized Method of Moments (GMM) regression has been implemented to examine the impact between the variables in the models. Empirically, the results show that Fama and French (2015) 5-factor model is the most consistent model in comparison to the other two models in terms of explaining the cross-section of average stock returns in Tadawul. However, it is not the best according to the intercepts results of all the regressions in 2x3, 2x2, or 2x2x2x2 sorts. Besides, Fama and French (2015) 5-factor model has the highest explanatory power in most of the portfolios based on the adjusted R2 regardless of the sort (2x3, 2x2, or 2x2x2x2). Finally, the results conclude that Fama and French (2015) 5-factor model can be an applicable model in Tadawul but only market and size can affect the stock returns, while the value, profitability, and investment cannot. Accordingly, the author recommends that, as a continuation of this research, further research can be done, which investigates a model with additional factors like momentum and illiquidity.

This paper examines momentum and contrarian effects in the Ukrainian stock market after one-day abnormal returns. To do this, UX futures data over the period 2010–2018 are used. The following hypotheses are tested: H1) hourly returns on overreaction days differ from hourly returns on normal days, H2) there are price patterns on overreaction days, and H3) to test these hypotheses, visual inspection and average analysis are used, as well as t-tests, cumulative abnormal returns, and trading simulation approaches. The results suggest that there are statistically significant differences between intraday dynamics during the usual days and the overreactions day. There is a strong momentum effect present on the day of overreaction: prices tend to change only in the direction of the overreaction during the whole day. The fact of the overreaction becomes clear after 13:00-14:00. This gives a lot of time to explore the momentum effect in the day of overreaction. On the day after the overreaction, prices tend to go in the opposite direction: contrarian pattern is detected, which is in line with the overreaction hypothesis. Based on detected price patterns, rules of trading and trading strategies for the Ukrainian stock market are developed. Momentum Strategy (based on price patterns on the day of overreaction) generates several successful trades; close to with 90%, and their number being is profitable (trading results differ from the random ones – confirmed by t-tests). Contrarian Strategy (based on price patterns on the day after the overreaction) demonstrates low efficiency, and results do not differ from random trading.