Examining the Presence of Weekend Effect Anomaly in Chinese Market

Abstract

In this thesis, the objective is to test the presence of weekend effect anomaly in the Chinese stock market by examining SSE Composite Index and SZSE Composite Index. There are five chapters in this thesis. Chapter Two is mainly about the literature background of this work. It gives efficient market hypotheses a more specific explanation and introduces many research results of several countries related to market anomalies tests, which will provide us some supports in the following comparison. In Chapter Three, we mainly introduce the data and methodology of tests. Data of daily returns are calculated by open-close price change and close-close price change. Then we use paired t-test, ANOVA test to see whether returns between each pair and among all weekdays exist significance difference. After that, we use regression analysis to show relationship between daily returns and each weekday. Dummies variable regression shows statistical results of linear relationship, and logistic regression tries to state the probabilistic model which can help to predict future returns. The main results are presented in the Chapter Four by using SPSS software. Besides, the detailed results will be shown in the Annexes. All data sources and calculation outcomes are stored in the CD attached to the final page. The last chapter is the conclusion of the whole thesis. It concludes not only the summary of previous results and comparison, but also some suggestions on the future further research.

In this thesis, the objective is to test the presence of weekend effect anomaly in the Chinese stock market by examining SSE Composite Index and SZSE Composite Index. There are five chapters in this thesis. Chapter Two is mainly about the literature background of this work. It gives efficient market hypotheses a more specific explanation and introduces many research results of several countries related to market anomalies tests, which will provide us some supports in the following comparison. In Chapter Three, we mainly introduce the data and methodology of tests. Data of daily returns are calculated by open-close price change and close-close price change. Then we use paired t-test, ANOVA test to see whether returns between each pair and among all weekdays exist significance difference. After that, we use regression analysis to show relationship between daily returns and each weekday. Dummies variable regression shows statistical results of linear relationship, and logistic regression tries to state the probabilistic model which can help to predict future returns. The main results are presented in the Chapter Four by using SPSS software. Besides, the detailed results will be shown in the Annexes. All data sources and calculation outcomes are stored in the CD attached to the final page. The last chapter is the conclusion of the whole thesis. It concludes not only the summary of previous results and comparison, but also some suggestions on the future further research.