Most prior research has tested for monthly regularities based on the Gregorian calendar; by contrast, little attention has been given to other calendars based on different religions or cultures. This paper examines Islamic monthly anomalies in a stock market located within a

Stock market trading is an activity in which investors need fast and accurate information to make effective decisions. Since many stocks are traded on a stock exchange, numerous factors influence the decision-making process. Moreover, the behaviour of stock prices is uncertain and hard to predict. For these reasons, stock price prediction is an important process and a challenging one. This leads to the research of finding the most effective prediction model that generates the most accurate prediction with the lowest error percentage. This paper reviews studies on machine learning techniques and algorithm employed to improve the accuracy of stock price prediction.

Studies have shown that religious beliefs and practice play an important role in influencing share price behaviour. Evidence of a Ramadan effect has been documented in Muslim countries suggesting an increase in mean returns as well as a reduction in volatility during the ninth month of the Islamic calendar. In addition to the Ramadan effect, studies have also documented a January effect in Muslim countries. The current study investigates what happens when the Ramadan effect and the January effect occur at the same time. Controlling for the effects of financial crises and time-varying volatility in returns, the results for individual company data from four countries with sizeable Muslim populations indicate higher returns and lower volatility when these two effects overlap, except in one, arguably more Western country, Turkey.

This article investigates whether economic variables have explanatory power for share returns in South Asian stock markets. In particular, using data for four South Asian emerging stock markets over the period 1998 -2012, the article examines the influence of a selection of local, regional and global economic variables in explaining equity returns; most previous studies that have examined this issue have tended to focus on only local and/or global factors.

This paper seeks to explain time-varying correlations among equity returns. The literature has shown that fundamental and economic factors can explain stock returns or the volatility of markets. Here, panel data analysis is employed to examine whether these factors can also explain the comovement of stock returns. Time-varying correlations among sectoral indexes are estimated using a restricted multivariate threshold GARCH model with dynamic conditional correlation (DCC-MTGARCH) controlling for the asymmetric effects of news and the influence of financial crises. The empirical results from this panel data analysis show that equity return correlations can be explained not only by macroeconomic variables but also by fundamentals within an industry. JEL classifications: C58; G12; G14; G17