January effect and testing for normality

This report explores the market anomaly called the January effect, which has been subject of much academic debate over the course of the last century with no firm conclusions being made. In order to be able to progress through the analysis of the January effect in a very organized fashion this report is divided into two parts. In the first part the theoretical grounding behind the January effect, its prolonged existence, and the econometric model designed to explore its existence is provided.

Additionally, the capital asset pricing model is discussed with relation to the January effect. Finally, basic results from the regression output are analyzed. In the second part, the findings and results of the econometric model used are interpreted and discussed with connection to the existence of the January effect in the markets chosen for study. Tests for non stationarity of the data, and the violations of the five core assumptions of the classical linear regression model are carried out and the results are interpreted.

Any discussion pertaining to the existence of the January effect finds its origins in the definition of the Efficient Market Hypothesis (EMH), which states that financial markets are at all times ‘efficient’. This means, that at any given time asset prices fully reflect all available information and are unbiased estimates of the true value of the asset. This implication leads to two conclusions; first, that it is not possible to regularly outperform the market, and second, that past price movements cannot be used to predict future price movements. Rather, prices follow what is known as a 'random walk' which is an intrinsically unpredictable pattern.