Any anomaly, including January Anomaly, would enable the investors and speculators to gain abnormal returns. The presence of January Anomaly defeats the basic premises of the efficient market hypothesis. Besides, it has greater implications for the design of investment strategy in the long run. This paper seeks to find out whether the 'January Anomaly', found in many countries, is also found in the fast developing Indian Markets. The study used the logarithmic data for S&P CNX Nifty and S&P CNX 500 sample indices and applied the Dummy Variable Regression Model from 1st April 2002 to 31st March 2011. It is found that the highest mean return was earned in December and the lowest/ negative mean return earned in January Month for S&P CNX Nifty index. The S&P CNX 500 Index recorded the Highest Mean Return in the Month of March and the Highest Negative Mean Returns in the Month of January. It is found that there was significant difference in the mean returns among the different months of the year. The analytical results of seasonality indicate the absence of January Anomaly during the study period.

India is one of the major emerging economies of the world and has witnessed tremendous economic growth over the last decades. The reforms in the financial sector were introduced to infuse energy and vibrancy into the process of economic growth. The Indian stock market now has the largest number of listed companies in the world. The phenomenal growth of the Indian equity market and its growing importance in the economy is indicated by the extent of market capitalization and the increasing integration of the Indian economy with the global economy. Various schools of thought explain the behaviour of stock returns. The Efficient Market Theory is the most important theory of the School of Neoclassical Finance based on rational expectation and no-trade argument. The book investigates the growth and efficiency of the Indian stock market in the theoretical framework of the Efficiency Market Hypothesis (EMH). The main objective of the present study is to examine the returns behaviour in the Indian equity market in the changed market environment. A detailed and rigorous analysis, made with the help of the sophisticated time series econometric models, is one of the key elements of this volume. The analysis empirically tests the random walk hypothesis and focuses on issues like nonlinear dynamics, structural breaks and long memory. It uses new and disaggregated data on recent reforms and changes in the market microstructure. The data on various indices including sectoral indices help in measuring the relative efficiency of the market and understanding how liquidity and market capitalization affect the efficiency of the market.

The efficiency of the capital market raises various issues all over the world. Earlier research studies give evidence that the capital markets are informational efficient and hence, cannot outperform the market consistently on the basis of price change predictions. However, some researchers have also brought into light seasonal effects/calendar anomalies in the developed markets. This paper investigates one such anomaly (Semi-month and Turn of the month effects) in an emerging Indian Capital Market. The S&P CNX Nifty and BSE Sensex Index data have been collected and analyzed for a period of six years from 1st January 2005 to 31st December 2010. The analysis of the study found that the semi-month and turn of the Month Effect not exists in Indian Stock Market during the study period.

This paper examines whether the 'January anomaly' or 'seasonality of monthly returns' found in several advanced markets is also found in the fast developing Indian markets. Any anomaly, which includes January anomaly or effect, would enable the investors and speculators to gain abnormal returns. Although the presence of January anomaly defeats the basic premises of the efficient market hypothesis, it has greater implications to design suitable investment strategies in the long run. We use the logarithmic data of the five most important indices of the National Stock Exchange of India (NSE) for the period from 1999 to 2007 and apply a set of selected statistical parameters to examine the presence of anomaly, if any, in the market. Our analytical results indicate the presence of 'January anomaly' in Samp;P CNX Nifty which is the benchmark index of the NSE. Kruskal-Wallis test shows statistically significant differences in monthly returns in respect of three indices while Wilcoxon-Mann-Whitney test reveals statistically significant differences in the month of April, November and December when compared to January returns. Dummy Variable Regression, yet another test applied to investigate the January anomaly, also reveals statistically significant results in monthly returns. Friedman Anova test suggests that seasonality in stock returns is present in the case of only one index, Samp;P Nifty Jr. Our findings corroborate the results of previous evidences documented in the literature. Our investigation further reveals that March and April turn significant negative returns but prove to be the potential months to buy the scrips (buy low); Contrary to this, November and December show significant positive high returns goading us to conclude that these two months are the best period to sell the securities (sell high). Tax-loss selling hypothesis and Accounting-information hypothesis could be the possible explanations for the anomalous behavior of the scrips in the Indian markets. In a nutshell, our results indicate that the Indian markets show evidences of seasonal anomalies and offer enormous opportunities to gain reasonable returns in the long-run.

The Efficient Market Hypothesis believes that it is impossible for an investor to outperform the market because all available information is already built into stock prices. However, some anomalies could persist in stock markets while some other anomalies could appear, disappear and re-appear again without any warning. A Special Issue on "Efficiency and Anomalies in Stock Markets" will be devoted to advancements in the theoretical development of market efficiency and anomaly in the Stock Market, as well as applications in Stock Market efficiency and anomalies.

The presence of the Seasonal or Monthly Effect in stock returns has been reported in several developed and emerging stock markets. This study investigates the existence of seasonality in India's stock market. The Efficient Market Hypothesis suggests that all securities are priced efficiently to fully reflect all the information intrinsic in the asset. The Seasonal Effects create higher or lower returns depending on the Time Series. They are called Anomalies because they cannot be explained by traditional asset pricing models. Examples of such patterns include e.g. the January Effect, the Day-of-the Week Effect and the Week of the Month Effect etc. Studies on the Seasonal Effects in the Indian Stock Market are limited. In an attempt to fill this gap, this study explores the Indian Stock Market's Efficiency in the 'weak form' in the context of Seasonal Effects. The objective of this paper is to explore the Seasonal Effect on the Indian Stock Market. For the purpose this analysis BSE Sensex index was chosen for a period of ten years from 1st April 2000 to 31st March 2010. The study found that the Day of the Week Effect and Monthly Effect Pattern did not appear to exist in the Indian Stock Market during the study period.