I shall name the ranking system the Trustamind Rank 1.0, or T-Rank 1.0, hereafter for convenience.
The idea comes from the StockGrader from MarketGrader.com. Barron's subscriber has free access to it. StockGrader evaluates the fundamental strength of a stock in four categories: growth, value, profitability, and cash flow. For each category, a letter grade is given based on the fundamental data such as P/E, P/S, etc. And the four letter grades sum up to a number grade that represents the fundamental quality of the stock. I was using it to guide my investment for about a year, trying to combine it with technical techniques such as resistance, support to determine entry and exit. Overall speaking, the performance is good. But sometime I got trapped into a position for a couple of months before its fundamental strength kicks in. I know I shouldn't complain for this as a fundamental investor, but I'm not satisfied.
So I was trying to come up with my own ranking system. I still want it to be based on pure fundamental indicators. Furthermore I want it to be short term oriented. That's why I enforced weekly rebalance. If it's profitable when the minimum holding period is just a week, I'd say my goal is accomplished.
Growth and value made good sense to me. But profitability and cash flow didn't, so I removed them. My short term perspective suggested to check the financial condition to make sure it won't go bankrupt in near future. So my ranking system has three categories with equal weight:
- Growth, 1/3;
- Valuation, 1/3;
- Financial condition, 1/3.
Lately I was heavily influenced by the blog posts and articles by Gannon, a knowledgeable and insightful fundamental investor and blogger. He suggested that return on capital is an important fundamental indicator, which usually includes RoC, RoE (return on equity), and RoI (return on investment). So I also add return on capital to the mix, but only give it half weight as I'm not familiar with it. Below is the final version. And now you know where the 7 comes from.
- Growth, 1/3.5 = 2/7;
- Valuation, 1/3.5;
- Financial condition, 1/3.5;
- Return on capital, 0.5/3.5.
The initial back test looks good as shown in an earlier post.
As a logical next step, it's worth to understand the contribution of each of the components. So I did a little bit research which I called Impact Analysis. I remove each category from the ranking system and see how the resulting APR changes. The greater the change, the greater the impact, thus the greater the contribution and significance the category bears. Actually this statement is not perfect, the contribution a category has comes in two folds: its own contribution and its interaction with other categories. It's possible that you have two indicators that each, when applied alone, has good performance, but when combined they works poorly.
The table below shows the result where the categories are ordered by their impact. Valuation is the most significant one, not a surprise. The second place holder is financial condition, which is explainable by the short term perspective. Then it comes to return on capital. It is to my surprise because it only has half weight, but I'm sure Gannon and other RoC advocators won't be surprised. The funny thing is that growth comes to the last. Not only that, it has a negative contribution, -3.46%, to the ranking system.
I know that I should respect the data, not my gut feeling. But this results is well beyond my imagination. I thought about it for a while and coined a theory to explain it. The theory is that, the market overly chased growth in the last decade. Consequently, the entire security analysis industry devoted a large portion of effort into forecasting growth. If you pay attention to those research reports, you'll see a lot stuff like this: research firm ABC upgraded stock XYZ as in the latest channel check they found that shipment increased by ijk%. So the growth is largely priced into the shares before it goes to the quarter or annul reports, and to us fundamental investors, the growth is a lagging indicator.
I'll start to work on T-Rank 2.0, to see whether I should simply remove growth or tune up its weight. I'll report my discovery shortly.