“Sell in May” Debunked?
This time every year the “sell in May and go away” strategy rears its head again.
It’s hard to buy in to the idea that such a simple approach could have such divining powers, but the results are (on the surface) compelling.
I’ve been pondering how best to put the strategy through the paces. Thoughts…
Usually a graph like the one above accompanies these discussions. Here I’ve shown the S&P 500 (dividend-adjusted) from Nov-Apr (red) vs May-Oct (grey), since 1950.
Awesome results. Great strategy.
The problem is of course that this is all prepared with the benefit of hindsight. Surely in 1950, we wouldn’t have known that Nov-Apr would turn out to be such fortuitous months for stocks. So in the next graph I’ve taken a different approach.
I’ve assumed that each year the investor only looked at the data available from 1930 up to that point in time, and invested in whatever 6 months of the year had been the best for stocks.
This is called “walking the test forward”, and (to some degree) removes the benefit of hindsight.
The graph shows that most of the benefit of choosing seasonally strong months disappears because the investor wouldn’t have made the “right” choices given the information available at that time.
The investor would have done well since the 1990’s, but that’s a much less robust observation than the first graph would imply.
. . . . .
So what if rather than choosing seasonally strong months based on ALL data available up to that point in time, the investor only looked at say the last 10 years?
If we go out to about 30 years (i.e. the investor is choosing seasonally strong months based on the previous 30 years of S&P 500 data), the strategy soars again…
But the fact that only 30 years (as opposed to say, 20) works so well is most likely because it’s a curve-fit solution.
So does the data totally debunk “sell in May”?
No. I wouldn’t base a trading decision solely on the rule, but results in all tests were impressive enough in recent history that the observation at least deserves to be on the radar.
But that really misses what I think is the more important point:
The graph like the first I showed would lead the reader to think that the “sell in May” rule is much more robust than it actually is. In truth the rule is at best a questionable observation, and at worst, simply a product of randomness.
P.S. This post isn’t meant to dump on the quantitative minds who I respect very much that have discussed this subject recently. I’m just one nerd with $0.02 and I recognize that on this one, I am probably out on a long branch all by myself.
. . . . .
Filed under: Time-based, Trading Strategies | 15 Comments