Clarification of Misconception on the Day of the Week Effect : Methodological Analysis*

What the paper says

IntroductionWe will examine the well studied day of the week effect, which is for many authors the effect that the day has on the daily differences of the general index. We will try to clarify differences between the day of the week effect (DWE) and the impact that the day has on the general index (GI) a point that many colleagues do not make clear in the analysis of their models. For example Wang, et al1, who showed that the well-known Monday effect is largely caused by the Mondays of the fourth and fifth weeks of the propose that investor should sell before the end of the third week or buy after the fourth Monday of the month. We believe that one can make such a suggestion only when studying the impact that the day has on the general index and not on daily differences of the general index (which they studied). A math analogy would be to confuse min and max of the first derivative of a function with the min and max of the function.Most authors, French2, Gibbons & Hess1, Rogalsky4, Choy and O'Hanlon5, Solnik and Bousquet6, Lakonishok & Maberly7, Dubois & Louvet8, Jaffe & Westerfield9, examine day of the week anomalies (examining trading time hypothesis, calendar time hypothesis, Monday phenomenon, weekend effect etc.) where, apart from other, they give results regarding the statistical significance on daily differences of the general index. That is the impact that factor day (of their models) has on the daily differences of general indexes. Who can benefit from such information? There is an obvious benefit for the day trader. Which would be the best day to buy or to sell common shares? In order to answer this question one needs to study the impact that day has on the general index and not the daily differences. We answer both questions later on in the paper.We provide an example in order for someone to better comprehend what most colleagues studied day of the week effect on daily differences and the impact that day has on the general index. Consider a hypothetical Dow Jones index where there is a repetitive mode and Monday is 1, Tuesday is 0, Wednesday is 1, Thursday is 1, Friday is 2(Table 1).Then of course since the minimum price is on Tuesday and the maximum price is on Friday, the advice one would give is to buy on a Tuesday and sell on a Friday with a profit of 2 units. However when we apply the daily differences transformation on the general index we get variable PER=(P^sub t^-P^sub t-1^).Hence the following values of the response (PER) will be: for Monday -1, for Tuesday -1, for Wednesday 1, for Thursday O and for Friday 1 (Table 1). One should not treat the transformed response PER the same as the Dow Jones index. The only conclusion (for profit making) that someone can make by looking at this transformed response is for one day trading buying on Tuesday and selling on Wednesday and buying on Thursday and selling on Friday. The usual transformations performed by most colleagues in order to examine DWE on daily differences include: P1XP1, or log (P^sub t^/P^sub t-1^) or (P^sub t^ + e)/P^sub t-1^ where P^sub t^ price of index on day t, P^sub t-1^ the price of index the previous day and e is a correction depending on the model used. Great attention should be paid when transforming the response to avoid misrepresentations like Lyroudi, et al10 where they present as the mean returns of GI the mean logarithmic daily differences.This paper will have the following objectives:* Use data for a very large period of time (1986-2006) for the ASE, since most researchers use periods of 5 to 10 years at most Alexakis, Xanthakis11, Koutmos, et al12, Mills, et al12, where we will try to examine the day of the week effect on daily differences and its relation to the month effect anomaly. For example if one is a day trader, is it better to invest on January's Fridays or February's Tuesdays?* Give results regarding the impact that day has on the GI of ASE. …