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Calendar Effects in the Pakistani Stock Market

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Calendar Effects in the Pakistani Stock Market
International Review of Business Research Papers Vol. 5 No. 1 January 2009, Pp. 389- 404

Calendar Effects in Pakistani Stock Market
Shahid Ali* And Muhammad Akbar**
The paper investigates calendar anomalies in the Pakistani stock market by taking a data of stock returns of fifteen years from November 1991 to October 2006. The existence of calendar anomalies could endanger the assumption of Efficient Market Hypothesis. Using one Factor ANOVA the main hypotheses about equality in returns on daily, weekly and monthly basis are tested using F-test and are found to be insignificant, Autoregressive Integrated Moving Averages ARIMA and Ordinary Least Squares OLS are also extended as an alternate procedure to look for any above average returns reaped by market players. An AR1 model is fitted on the data along with a simple linear regression model to test the slopes. Before using an estimated equation for our stated hypotheses an examination of residuals is made for evidence of serial correlation using the Durbin-Watson statistic. Anderson-Darling test of normality is applied as a prerequisite before computing interval estimates and using the one factor ANOVA. The study concludes that there are no weekly effects or monthly effects in stock returns in Pakistani equity market however the market is inefficient in the short run and there is existence of daily effects where the fourth and fifty days of a week show abnormal returns using autoregressive modeling.

1. Introduction Calendar effects have remained as an area of growing interest for researchers in the last three decades as the presence of the phenomena has been evidenced even in the most developed capital markets of the world. Calendar effects are the stock price anomalies that are attributed to calendar. Day-of-the- week, the end of the month, the month of the year and holidays’ effects are the most prominent of these stock price anomalies. According to the theory of Efficient Market Hypothesis stock prices



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