In part 1 of the series I showed the impressive predictive power of day of the month seasonality effects in US equity markets. In this post I will apply the same type of analysis to three European markets: Germany (using the DAX index), France (using the CAC 40 index), and the U.K. (using the FTSE 100 index). Once again I must note that day of the month effects by themselves do not constitute a trading strategy, but I believe that the impressive returns predictability can be used to enhance other trading approaches, both systematic and discretionary.
The methodology:
The European indices have a far shorter history than the US ones, so we need to limit the look-back period in order to get a useful sample size. As such, I have slightly modified the approach to use less data in the early parts of the sample.
- Standardize every month to 21 trading days; round to the nearest integer when the number of days in a month is different.
- Start by using the last 2500 days; keep increasing the sample size until you reach 5000 days. After that use a moving window of the last 5000 days of daily returns and estimate the average return on every (standardized) day of the month.
- Rank the days by their past returns. If the next day is in the top 6, buy on close and sell on the next close.
- Move forward by one trading day and repeat from step 2.
The results:
DAX:
The equity curves:
And the statistics:
CAC 40:
The equity curve:
And the statistics:
FTSE 100:
The equity curves:
And the statistics:
Calendars:
One of the results that stands out is that the 15th day of the month seems to be absolutely terrible in every market. This is doubly peculiar because while the best days seem to be different for every market, the worst ones are consistent across the board. I would love to hear some theories about this.
In any case, day of the month seasonality effects are incredibly powerful in European markets as well. They’ve managed to provide positive returns in essentially all market environments. The fact that the best days occur on different parts of the month depending on which market you look at is amazing: it means there are more opportunities out there to exploit if you’ve got capital lying around.
In the next (and for now, final) part of the series, I will look how these seasonality effects hold up in Asian markets.
Christian Rolfsson says:
It looks like all the markets have declined in your test period so there is a bias towards red… and isn’t options expiration around 15th trading day? That day is usually not a strong day if I remember correctly.
qusma says:
Option expiration day can be between the 10th and the 15th, on average it’s the 13th.
During the last decade options expiration day has actually been slightly above average in terms of returns for the US markets. In particular the overnight returns into options expiration day are quite consistently good, whereas the RTH returns are slightly negative. It tends to be really bad during bear markets though (filtered depending on price is above/below 200DMA).
2013: Lessons Learned and Revisiting Some Studies says:
[…] done 3 posts on day of the month seasonality (US, EU, Asia), and on average the DOTM effect did its job this year. There are some cases where the top […]