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By identifying the presence of the calendar/seasonal anomalies impact on the market, this article looked at the efficiency of Pakistan's numerous stock indices. This study's data spans a ten-year period, from January 2011 to December 2020. The January effect, negative Monday impact, and semi-month effect are investigated using statistical models such as the Ordinary Least Square (OLS) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, as well as the Lagrange Multiplier test to determine if the data set is heteroscedastic. The result demonstrates the Pakistan Stock Market's inefficiency as well as the occurrence of calendar/seasonal anomalies such as the January impact, negative Monday effect, and semi-month effect. In addition, the Wednesday results are among the most notable finds as it was the most significant, and the one with the greatest average mean returns. The months of June and July were found to be non-significant, indicating that the tax loss hypothesis does not hold. The finding of the study proved the inefficiency of the Pakistan Stock Exchange and the findings on seasonal anomalies can help investors of Pakistan Stock Exchange gain abnormal returns.

Keywords: Seasonal Calendar Anomalies, January Effect, Negative Monday Effect, Semi Month Effect, Heteroscedasticity.