JultikaUniversity of Oulu repository

Abstract

This study aims to examine the presence of three well-documented calendar anomalies: The January/monthly, turn-of-the-month and day-of-the-week effect. These anomalies refer to systematic variations of financial asset returns during certain times of the week, month, or year. Throughout decades, these stock return regularities have been considered as decisive counterexamples that deviate from efficient market hypothesis due to potential trading strategies that generate abnormal returns based on such seasonal variations.

Most explanations on the appearance of calendar anomalies are related to behavioural finance framework. Thus, investors might base their investment decisions on behavioural characteristics such as overconfidence and loss avoidance. However, recent research suggests that seasonal effects are disappearing in stock markets. The disappearance of calendar anomalies is a result of market learning, and therefore the exploitation of stock return seasonality has become less prominent. Based on the market efficiency theory, behavioural anomalies should be arbitraged away in the long run when investors begin exploiting them (Fama, 1998).

This thesis aims to examine the behavior of stock return seasonality in six emerging market exchanges during the period of January 2005 through December 2020. Since numerous emerging market exchanges are open for foreign investors and they have experienced a rapid growth in recent years, the interest of observable anomalies is highlighted. The widely popular January/monthly, turn-of-the-month and day-of-the-week effects are estimated with the commonly used dummy variable regression model. In addition, all three are estimated with the GARCH framework by incorporating volatility clustering and asymmetric responses of return volatility.

The OLS results show that the turn-of-the-month effect is statistically significant in Prague, Budapest, and Malaysian stock exchanges. The effect is also significant based on the GARCH regression results. Moreover, based on the OLS results, a weekend effect is found in the Malaysian stock exchange, where Friday returns are significantly high, and Monday returns significantly low. Under the GARCH framework, a January effect is found only in the Prague stock exchange. This indicates that the anomaly has most likely disappeared. Furthermore, the GARCH regression results exhibit positive Monday effects for Prague, Warsaw, and Johannesburg exchanges. Thus, the mixed results of the January/monthly effect and the day-of-the-effect indicate that they are sensible to the choice of error distribution, and generalizations of their existence cannot be made. However, the asymmetric GARCH models exhibit similar results by accounting the volatility dynamics to a greater extend. Thus, seasonality in the examined emerging market returns is present.