August 30, 2018
Recently on Quantopian, one of the topics was: Common Factor Risk Snapshot. The provided notebook's intention was to give a quick snapshot of the performance of common risk factors over the past year.
The following chart (Cumulative Sector Factor Returns) is based on Maxwell Margenot's notebook which can be found HERE.
|Cumulative Sector Factor Returns|
(click to enlarge)
The chart is a look at the bigger picture, a change in perspective. If you want to design stock trading strategies that can last, maybe we should start by looking at longer trading intervals than just one year.
The chart uses the same code as with Maxwell's 1-year chart. I only requested it to consider the last 10 years, see code line: last_year = dt.datetime.today() - dt.timedelta(weeks=52*10).
From the above chart, we can see a definite underlying upward trend in these sector return factors. They stayed in about the same relative order throughout. In fact, the top 5 remained the top 5 from 2012 onward (over 6 years, 1,500+ trading days).
You can have factor variations on a 1-year rolling window (as illustrated in Maxwell's chart), but they do not offer much in predictability since from one year to the next that 1-year window might look quite different. The same would apply if you shorten the rolling window to say 9 to 6 or to 3 months.
It is more like as if looking at the trees from too close when you should zoom out to see more of the forest.
However, if you continuously extended that first 1-year window, leaders would take hold and ride their upward trends, maintaining their ranking for long-time intervals. Therefore, if you had to make any predictions, it should have been in the same direction as those lines and not in predicting, every other day, a reversal to the mean which did not happen.
If you compare your trading strategy's mean-reversal style factor to something that did not mean-reverse, does it not make your style factor almost irrelevant? Do you want to show that over your investment period mean-reversal worked, even if it didn't, or are you in it for the money? That too is a choice someone has to make.
The best sector performance levels, evidently, were on the top few lines. The others should be considered as also ran, right down to the bottom line. If someone had to make a choice, they should have followed the leaders. That is where the best returns were.
This could have been done by periodically monitoring the sector leaders for the highest performances. And within the few leading sectors, select the best-performing stocks. Easy to detect, they were outperforming the averages. And, if your selected stocks were outperforming the averages, then collectively, they would also outperform the averages. And bang, “alphatos gratos”.
Questions and Observations
Where is the sector-rotation thing in this? It would appear as if since 2012 the market forgot the whole group of sector-rotationists. From 2012 on, there seems to be little to be gained in the sector-rotation business.
All sectors are not equal. Right, and they do not oscillate and mean-reverse around the zero return line all the time either? In fact, they tended to do as if most had aspirations for a better world (read trend upward).
What! These things did not mean-reverse during that period. You must be kidding. These things mean-reverse all the time. There is not much evidence of that in the above chart. But, you should make your own conclusions. I'm just providing the chart.
So, I am saying: one should have followed the best performing sectors since that is where the money was flowing. Yes, and as in many things, follow the money. It's right until its wrong. And in this case, it has been right for at least the past 6 years. You are still in this game to win as much as you possibly can. The first step might be to play the best out there showing the most prospects.
Note the above chart reflects what we see in the market. If you wanted to use market indexes or sector ETFs instead, the chart would have about the same look and design.
Can we deduce all that from a chart? Yes, we just did.
Created... August 30, 2018, © Guy R. Fleury. All rights reserved