All,
This is my first post documenting my exploration of the Core Combination ranking system. I decided to use that ranking system as a learning exercise as anything else. Eventually, I wanted to examine the individual components.
I used as my stock universe the S&P 1500. The reason is that some of my investing friends were not interested in trading small caps and micro caps, fearing that a small company could go under suddenly. While I knew that the best performing screen on AAII over the entire period they examined was “O’Shaughnessy: Tiny Titans Screen” (see https://www.aaii.com/stockideas/allstrategies), I also knew that the second best screen, “Est Rev: Up 5% Screen”, covered stocks of all sizes, not just small cap stocks. So I figured that the S&P 1500 was a good start.
I wanted to consider as wide a time as possible, as I wanted to see how it performed under different market conditions. I didn’t want to use a ranking method that performed great in one market regime but awful in others. I used the longest time period I could, which was 01/01/2002 to what was then the present, 07/02/2022. (More on this test period later.)
I then ran the simulation. I don’t remember what it was but I was not impressed. I was running a small portfolio of 5 stocks. I decided to change the sell rule from “Rank < 60” to “Rank < 90”. My reasoning was that for every stock I hold represents an opportunity cost as well as an opportunity. If I am holding a stock that ranks, say, 62, then that means that in the S&P1500 universe, there are ((1-.62)*1500=) 570 stocks that rank higher than the stock I am holding. Holding that stock is an opportunity cost, just like a value trap type stock. So with the “Rank < 90” rule in place, I ran the test again and got substantially better results. Hmmm, let’s try it with “Rank < 95”. I got even better results. Then I tried “Rank < 98”. I got worse results. So, I chose to set my sell rule to “Rank < 95”.
So with these rules in place, here are the results I got using the original Core Combination ranking system. I have also included the results of holding 25 stocks based on comments from Ryan Telford (“rtelford”) to my post “Texas Aggie(*) I/Q getting in the way - why are my tranches so different?”
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all factors, original weights … 5 stocks … 25 stocks
----------------------------- … --------- … ---------
Total Return … 564.38% … 921.61%
Benchmark Return … 393.03% … 393.03%
Active Return … 171.35% … 528.57%
Annualized Return … 9.68% … 12.01%
Annual Turnover … 77.91% … 132.93%
Max Drawdown … -54.42% … -57.71%
Benchmark Max Drawdown … -55.19% … -55.19%
Overall Winners … (50/93) 53.00% … (433/774) 55.00%
Sharpe Ratio … 0.50 … 0.68
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Over a 20+ year period, the strategy earned 9.68%. While that is better than what the S&P 500 did, 29 screens at AAII did better than that over the same 20 year period. So obviously this ranking system is simply meant as a starting point and not necessarily to be used as-is. I decided to look at each of the six major factor sets (growth, low volatility, etc.) to see how each performed had I only used that factor set. The results will be in part 2.
Cary