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Muslim’s hope that the holy month of Ramadan will create something more valuable for them. Through fasting and good actions, they can get rewarded twice than they normally can achieve. With this motivation, the purpose of this paper is to investigate the holy month of Ramadan effect on the returns and volatility of the Shariah index in India.

Using the ordinary least square methods, this paper examines the impact of Ramadan effect on the returns of the Shariah index in India. This paper further investigates the impact of the holy month of Ramadan effect on the volatility of the Shariah index by applying GARCH-modified models. This paper categorizes the Ramadan days into three parts, namely God’s Mercy, God’s Forgiveness and Emancipation from hellfire to examine the relationship between the Ramadan effect and the returns and volatility of the Shariah index in India.

The results show that the returns during the month of Ramadan as a whole are statistically significant. The results further motivate that its last ten days have high influences than other days over the period. Finally, the study examines the Ramadan effect on volatility by applying GARCH modified models and finds an evidence of Ramadan effect during the first ten days of Ramadan month.

The positive impact of Ramadan increases on the days associated with higher worship intensity. The study provides an important information to the ethical investors to invest in the Shariah stocks during Ramadan days. This information is very useful for the investors to get an abnormal return during the Ramadan days.

The purpose of this paper is to examine the behavior of the stock market returns in the different days of the week and different months of the year in accordance with the Islamic calendar. Further, the study estimates the risk-adjusted returns to test the performance of the indices during the Ramadan and non-Ramadan days. Finally, the study investigates the impact of Ramadan on the returns and the volatility of the stock market indices in India.

Initially, the study applies the Ordinary Least Square method to test the day-of-the-week and the month-of-the-year effect of the common and Shariah indices. Next, the study employs the risk-adjusted measurement to examine the underperformance and over-performance of the indices for both the periods. Finally, the study estimates the GARCH (1,1) and GJR-GARCH (1,1) models to observe the impact of Ramadan on the returns and the volatility of the Shariah indices in India.

The study finds that an average return of the indices during the Ramadan days are higher than non-Ramadan days. Further, the average returns of the Shariah indices are significantly higher on Wednesday than other days of the week. In addition, the highest and significant mean returns and mean risk-adjusted returns of the indices during the Ramadan days are observed. Finally, the study finds an evidence of the Ramadan effect on the returns and volatility of the indices in India.

The study observes evidence that the Ramadan effect influences the Shariah indices, but not the common indices in the stock market of the non-Muslim countries. It indicates that the Ramadan creates the positive mood and emotions in the investors buying and selling activities. The study suggests that investors can buy the shares before Ramadan period and sell them during the Ramadan days to get an abnormal return in the emerging markets.

The purpose of this paper is to investigate whether the investor attention using the Google search volume index (GSVI) can be used to forecast stock returns. The authors also find the answer to whether the “price pressure hypothesis” would hold true for the Indian stock market.

The authors employ a more recent fully balanced panel data for the period from July 2012 to Jun 2017 (260 weeks) of observations for companies of NIFTY 50 of the National Stock Exchange in the Indian stock market. The authors are motivated by Tetlock (2007) and Bijl et al. (2016) to employ regression approach of econometric estimation.

The authors find that high Google search volumes lead to positive returns. More precisely, the high Google search volumes predict positive and significant returns in the subsequent fourth and fifth weeks. The GSVI performs as an useful predictor of the direction as well as the magnitude of the excess returns. The higher quantiles of the GSVI have corresponding higher excess returns. The authors notice that the domestic investor searches are correlated with higher excess returns than the worldwide investor searches. The findings imply that the signals from the search volume data could be of help in the construction of profitable trading strategies.

To the best of the authors knowledge, no paper has examined the relationship between Google search intensity and stock-trading behavior in the Indian stock market. The authors use a more recent data for the period from 2012 to 2017 to investigate whether search query data on company names can be used to predict weekly stock returns for individual firms. This study complements the prior studies by investigating the relationship between search intensity and stock-trading behavior in the Indian stock market.