The stock markets have always been an exciting field for theories and analyses of all kinds. In addition to numerous academic models, there are also simple, practical observations that never cease to amaze. The Turn of the Month (TOM) effect is definitely one of them. It was first introduced in the mid-1970s in the book "Stock Market Logic". In it, Norman G. Fosback examined the performance of the US stock market on the last trading day of a month and on the first four trading days of the next month. The result of his analysis, which covered the period from 1928 to 1975, was indeed sensational:
US stock market 1928-1975
An investor who had invested $10,000 exclusively in stocks on those five days around the turn of the month, and safely in interest during the rest of the time, increased his capital to a substantial $572,020.
The person who had invested the same amount in the stock market outside these five trading days lost most of his assets, which in the end amounted to only 899 dollars.
Can the TOM effect be scientifically proven?
In recent years, this astonishing result has prompted numerous scientists to take a closer look at the TOM effect. As early as 1988, a study by Josef Iakonishok and Seymour Smidt confirmed that the TOM effect was consistently observed on the US stock markets (basis: Dow Jones Industrials) between 1897 and 1986. The period for the change of month was defined as the last trading day of the "old" month and the first three days of the "new" month. The result was clear: The average return on these four trading days was 0.473 per cent, while the average month generated a return of only 0.349 per cent.
The fact that the TOM effect can also be observed after 1986 is proven by the researchers Xu and McConnell in their study "Equity returns at the turn of the month" from 2006. Here, the research duo used the same parameters as a basis for calculating the performance, so that the results are comparable. Figure 1 shows impressively that even after 1986 the majority of US stock market returns were actually achieved around the turn of the month. Incidentally, this is true even if extreme exceptions are not taken into account.
Do region and market capitalisation matter?
Another study on the TOM effect by Shamman Ramsundhar was written in 2008. Ramsundhar examined price histories from 1963 to 2008, also with regard to possible differences between small caps and large caps. The most important results are:
Between 1963 and 1981, the average return around the turn of the month was 0.108 per cent (large caps) and 0.172 per cent (small caps)
Between 1982 and 2008, the average return around the turn of the month was 0.112 percent (large caps) and 0.151 percent (small caps)
Over the entire period under review, the TOM return averaged 0.11 per cent (large caps) and 0.16 per cent (small caps)
The average returns for the remaining trading days were significantly lower - for both small caps and large caps
The TOM effect is also robust when it comes to possible regional differences: an analysis in which a total of 34 country indices were examined in the period 1969 to 1990 shows that this calendar effect - albeit with varying degrees of intensity - is a global phenomenon and is not limited to the US stock markets. Figure 2 shows the average daily returns of selected countries and impressively demonstrates how strong the TOM effect is in some cases.
Explanatory approaches are not convincing
When dealing with the TOM effect, sooner or later the question arises as to the causes that could explain such a price anomaly. Several theories circulate in the academic literature. The first explanation assumes that the payment of wages, salaries, interest as well as dividends and other types of income at the end of the month leads many market participants to invest these funds around the turn of the month and thus ensure above-average returns in this period. The research duo McConnell and Xu investigated this hypothesis in 2008 and came to the following conclusion: First, there was no evidence of an increase in trading volume on the NYSE during the turn of the month - on the contrary, the volume was even slightly lower than during the rest of the month. Moreover, this hypothesis also proved to be unsound when analysing inflows and outflows in equity funds; finally, no particular pattern around the turn of the month could be identified. Two further aspects - the size of market capitalisation and volatility - also speak against the assumption. The TOM effect occurs both with large caps and small caps, and at the same time volatility is not higher around the turn of the month, but again,even somewhat lower.
Will the price anomaly become shorter or disappear altogether?
A study by the University of Valencia (Link: Calendar Anomalies in Stock Index Futures by Oscar Carchano, Ángel Pardo Tornero :: SSRN) examined a total of 188 cyclical price anomalies for the S&P 500, DAX and Nikkei 225 futures for the period 1991 to 2008, including the turn-of-the-month effect. Here, a bootstrap and Monte Carlo procedure was used to test whether the respective pattern has statistical and economic (i.e. with consideration of trading costs) significance. The only calendar effect that turned out to be statistically significant in both periods examined was the "first trading of the month" for the S&P 500 Future.
This shows that the price anomaly has weakened to a certain degree, or more precisely, that it has a shorter duration: from several days that bring above-average returns, only one day remains. This observation is plausible, as it is in line with the theory according to which a certain price anomaly loses its effect or disappears altogether over time as market efficiency increases.
Let us note: For decades, above-average returns have been observed on the stock markets in the days around the turn of the month. According to scientific studies, this is a statistically significant and global phenomenon. Contrary to the assumption that such a price anomaly, which has been observed for decades, would disappear after a certain time, this calendar effect still exists today - albeit in a weakened form. Although there are numerous explanations in the literature for the causes behind this effect, they do not stand up to empirical investigation. So the mystery is and remains unsolved.