USING PIVOT TABLE TO TEST MARKET ANOMALY.

• Author: Branch, Ben

INTRODUCTION

The efficient market hypothesis (EMH) has been an essential concept in modern finance (Fama & Malkiel, 1970; Basu, 1977; Brenner, 1979; Losey & Talbott, 1980). There have been exceptions, called anomalies, to the weak form of the EMH. One glaring example is the January Effect. The January Effect states that the month of January historically seems to have generated abnormal rate of return in the stock market. Even though finance professors discuss market anomalies such as the January Effect in almost every investment class, few, if any, require the student to test the anomaly with real data, particularly at the undergraduate level.

The reason for the lack of testing is simple. Using conventional method requires the student to have working knowledge of programing skills, which most undergraduate students do not. Even if the students have the skill, it is still too time consuming for the professor to demonstrate the process in a typical undergraduate class setting. Practitioners face the same dilemma.

An apparent gap exists in the finance field for taking advantage of the power of pivot table. The authors of this study attemp to fill this gap by using pivot table to extend the test of January effect. They propose an easy-to-learn method for the task, pivot table. Pivot table is a tool widely used by marketing professionals for its powerful yet straightforward data-handling capacity.

Using pivot table is no more than a few mouse clicks. Contained in every Microsoft Office Excel program, pivot table is also the most practical tool. The authors conduct analysis of the January effect on possible paradigm shift, while demonstrating how students and practitioners can quickly learn to test market anomaly with pivot table. The process and its four steps (data download, data preparation, generating pivot tables and hypothesis testing) will be described in the testing process section.

LITERATURE REVIEW

The Efficient Market Hypothesis (EMH) was first formulated in Eugene Fama's Ph.D. dissertation in the 1960s and then appeared in an academic journal in 1970 (Fama & Malkiel, 1970). Since then, the EMH has become one of the cornerstones in modern financial theories. There has been ample evidence to support the weak form of the EMH, which states that security prices fully reflect historical prices at any given time (Fama & Malkiel, 1970; Basu, 1977; Brenner, 1979; Losey & Talbott, 1980).

Studies have shown exceptions to the weak form of the EMH, called market anomalies, and the most widely discussed anomaly is arguably the January Effect. An abundance of literature exists on the January effect. First reported by Sidney Wachtel in 1942 (Wachtel, 1942) and later studied by many (Jones, Pearce, & Wilson, 1987; Thaler, 1987; Jones, Lee, & Apenbrink, 1991; Bhardwaj & Brooks, 1992; Keamer, 1994; Haugen & Jorion, 1996; Haug & Hirschey, 2006), the abnormal return reported in the month of January seems to have been a persistent market anomaly.

The first study on the January Effect was published in 1942, long before the birth of the EMH. Sidney Wachtel (1942) did not specifically use the term "January Effect" in his study, considered by many the original report on the January Effect, but instead described "seasonal movements in security prices" in the December to January period.

Since Fama and Malkiel (1970) officially introduced the concept of the efficient market hypothesis (EMH), literature on market anomalies quickly exploded, becoming one of the dominant themes in finance academic discussions. Notable studies in the Journal of Finance alone include Schultz (1985), Jones, Pearce, and Wilson (1987), Seyhun (1988), Ogden (1990), Jones, Lee, and Apenbrink (1991), Bhardwaj and Brooks (1992), Keamer (1994), Starks, Yong, and Zheng (2006), and Haug and Hirschey (2006).

In one of the earlier studies, Schultz (1985) finds a January Effect for the 1918 - 1929 period on small firms' returns. Seyhun (1988) tries to offer two explanations for the January effect, one "...due to price pressure from predictable seasonal changes in the demand for different securities", and the other representing "compensation for the increased risk of trading against informed traders." Ogden (1990) reports that the January Effect is partially due to the varying "stringency of the monetary policy." Bhardwaj and Brooks (1992) reports that the January Effect found in previous studies "is not persistent, and thereby, not likely to be exploitable by typical investors." By utilizing a multifactor model, Keamer (1994) studies the seasonality in macroeconomy and seems to have found a link between the abnormal returns in January and seasonality in macroeconomic factors.

Attempt has been made to link the January effect with tax selling in December and the ensuing rebound in January (Branch, 1977; Jones, Pearce, & Wilson, 1987). Jones, Lee, and Apenbrink (1991) report that January Effect was insignificant prior to 1917, when personal income tax was introduced. The study indirectly confirms that the January Effect was tax related. In one of the most recent studies, Starks, Yong, and Zheng (2006) study closed end funds on municipal bonds and confirm that the...