Semi-monthly effect in stock returns: new evidence from Bombay Stock Exchange

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.

International investors’ interest in the capital markets in the region of Gulf countries has dramatically increased in last two decades. Thus, it would be motivating to investigate their characteristics, where the January anomaly is a major one. This paper studies the veracity of the January effect rule in the Gulf Cooperation Council (GCC) stock markets and examines the predictive power of January returns. Seven GCC stock markets are tested – the market indices in Bahrain, Abu Dhabi, Dubai, Kuwait, Oman, Qatar, and Saudi Arabia – from January 1, 2001 until December 31, 2018, a timeframe which has rarely been analyzed. Ordinary least square (OLS)-based dummy variable regression equation was used as the conventional econometric procedure in the works of financial calendar anomalies in stock markets. Some evidence is reported for the markets of Dubai and Kuwait. The paper also provides an additional explanation for the performance of stock market of Kuwait. The findings are opposite to the well documented evidence that emerging markets are less efficient and hence it is likely that several market anomalies are further pronounced. The results suggest that the predictive power of the January anomaly can be considered as a temporary anomaly in the GCC markets, since it is concentrated in only a couple of GCC markets and does not persist in time.

This study delves into the dynamic interplay between economic value added (EVA) and dividend payout among listed firms in India. Leveraging data spanning from 2013 to 2019 for 564 Indian-listed companies, the study employs a fixed effect panel regression model to meticulously examine the intricate relationship between EVA and dividend payout. The findings decisively indicate a significant and positive correlation between the two, underscoring that an augmented EVA is associated with an elevated dividend payout ratio. Notably, a compelling insight emerges, revealing that a 100 percent surge in EVA corresponds to a noteworthy 5 percent upswing in firms’ dividend payouts. To fortify the robustness of these findings, the study employs the Generalized Method of Moments (GMM) methodology, corroborating the initial results. In essence, this paper solidifies the notion that heightened economic value added translates to increased dividend payments, providing valuable insights for both practitioners and researchers in the realm of corporate finance.