The presence of the seasonal or monthly effect in stock returns has been reported in several developed and emerging stock markets. The Efficient Market Hypothesis (EMH) suggests that asset prices reflect on all obtainable information (Fama,1970). However, many studies have accepted not only that stock prices are predictable based on the preceding information, but also that indicators such as dividend yields, and gross domestic product contain information that is useful in predicting stock prices. This evidence is commonly called calendar anomalies. Calendar anomalies refer to the tendency of stock market returns to show systematic patterns at a certain time of the day, week, month or year. The existence of the calendar anomalies is a denial of the weak form of efficient market hypothesis which states that the stock returns are time invariant. This paper provides a new and economically plausible explanation for turn-of-the-month anomaly. It covers the post reform period. The study uses the monthly return data of the BSE healthcare Index from 1 April 2002 to 31 March 2016 for analysis. After examining the stationarity of the return series, we specify a linear regression model to find the turn of the month effect. The results confirm the existence of seasonality in stock returns in India. The findings are also consistent with the ‘tax-loss selling’ hypothesis. The results of the study imply that the stock market in India is inefficient, and hence, investors can time their share investments to improve returns. We find that the turn-of-the-month effect still exists, but its occurrence has moved to earlier dates. We also find that investment made on days before the turn-of-the-month performs better than those made during the turn-of-the-month. Simple time diversification strategy of spreading investment throughout the month, which doesn’t require a perfect foresight, is also found to generate a better performance.
Turn of the Month effect, healthcare Index, Stock returns, Linear Regression, Strategy
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