“Sell In May” – Particularly In Mid-Term Election Years

Last week I discussed that the month of April wraps up the “seasonally strong”investment period of the year and leads two of the weakest months of the year.

As the markets roll into the early summer months May and June tend to be some of weakest months of the year along with September.  This is where the old adage of “Sell In May” is derived from.  Of course, while not every summer period has been a dud, history shows that being invested during summer months is a “hit or miss” bet at best.

However, before you slip into a warm bath of investment bliss, it is important to remember that just because the data suggests that April will “probably” be a positive return month for the market, there is also the “possibility” it will not.  With a ratio of 43 losing months to 72 positive one, there is a 37% chance that April will yield a negative return.

In this past weekend’s newsletter, we took this analysis to the next step looking at the statistics behind the old adage “Sell In May And Go Away.”

As the markets roll into the early summer months May and June tend to be some of weakest months of the year along with September. This is where the old adage of “Sell In May” is derived from. Of course, while not every summer period has been a dud, history does show that being invested during summer months is a “hit or miss” bet at best as shown in the table to the left (click to expand).

However, there are many academic studies going back to the 1970’s which have confirmed the pattern as well.  As Sy Harding, via Financial Sense, recently noted an an academic study published in the American Economic Review in 2002 concluded that,

“Surprisingly, we found this inherited wisdom of Sell in May to be true in 36 of 37 developed and emerging markets. Evidence shows that, in the United Kingdom, the seasonal effect has been noticeable since the year 1694. The additional risk-adjusted outperformance [over buy and hold] ranges between 1.5% and 8.9% annually, depending on the country being considered. The effect is robust over time, economically significant, unlikely to be caused by data-mining, and not related to taking excessive risk.”