Stock Market Anomalies

This study examines whether the Indian stock market is efficient in semi-strong form and seasonality exists. For this purpose, we take the first and fourth quarters " results of companies for the years 2008 to 2011. We divide companies into good news and bad news portfolios on the basis of percentage changes in net profits and net sales. We use event study methodology. The results reveal that average abnormal returns occur randomly and cumulative average abnormal returns are significant for both portfolios. Fourth quarter results give better positive signals to the market than first quarter results. We conclude that seasonality exists in the Indian stock market and it is also semi-strong form inefficient and investors can use this opportunity to buy and earn abnormal profit.

The objective of this paper is to explore, using UK stock price data, the influence of Tobin’s q ratio on the cross-sectional variation of average stock returns. In contrast to Fama and French’s (1992) US study, we found that for the London Stock Exchange β on its own was a significant explanator of cross-sectional returns differences of expected returns at the individual stock level. However, when Tobin’s q, β, market value of equity and book to market equity were used as explanatory variables, we found only Tobin’s q and market value of equity were significant, and of these two, Tobin’s q had the higher explanatory power. This suggests that Tobin’s q has a particular important role as an indicator of future market performance, with stocks that exhibit a smaller Tobin’s q yielding a higher average return subsequently. We explain this effect on the basis of the risk proxy effects of Tobin’s q and link it with Hecht’s (2000) view on firm wide as opposed to equity only effects.

The existence of market return anomalies has long been recognized in the finance literature. Several studies have documented the effects of size, dividend yields, EIP ratios, book-to-market value ratios, weekend, and turn of the year (January effect) on market returns. Still, much controversy surrounds the existence of and explanations for the observed market anomalies. This study uses 1987-92 returns data to help provide more current evidence concerning market anomalies. A multivariate regression model (MVRM) is used to test for the presence of size effect, weekend effect, and January effect in this period. Evidence indicates the existence of a January effect for small firms, but other effects are not detected at any significant level.

There is an ongoing discussion if the 'sell in May' strategy, that prescribes stock investments only during the months from September to May, offers a higher profit than a buy-and-hold strategy throughout the whole year. In the literature, some empirical evidence is particularly found for several emerging markets. In comparison to the US stock market, we examine the profitability of the 'sell in May' strategy at the Russian stock market and analyze its risk-return trade-off. Additional emphasis is laid on the persistence of the corresponding returns.

The presence of seasonality in stock returns violates the weak form of market efficiency because equity prices are no longer random and can be predicted based on past pattern. This facilitates market participants to devise trading strategy which could fetch abnormal returns on the basis of past pattern. Fluctuations in the stock returns of firms listed at Nairobi Securities exchange motivated this study. In the Kenyan context, studies conducted on market anomalies in different markets have continued to yield different results in the majority of the investigated markets including the Nairobi Securities Exchange. This paper examines whether there is a significant variation in the average daily stock returns at the NSE and compares the findings to the previous empirical works on the topic. The paper tested for the presence of the Monday effect, differences in mean return across the five trading days, January effect, differences in the mean return across the five trading months and also provided the day-today and year-to-year behavior of stock return at the NSE. The study employed daily data from the year 2001 to 2015 to do analysis. The method of analysis was t tests and ANOVA. Policy recommendations are afterwards presented to aide the investors in making key investment decisions.

This paper serves as a brief communication of new empirical results on Vietnam stock market, the Ho Chi Minh City-based Securities Trading Center (HSTC). We will skip much of the information on the technicalities and description of the market, to mainly focus on the empirical results.