Evaluating Stocks Like Products: The Scoring Engine
In a previous post I described the framework: a quantitative lens for timing and a qualitative lens for conviction. What I didn't show was the machinery underneath. Here it is.
Every stock gets two scores, each on a one-to-five scale. The quantitative score captures the financial picture. The strategic score captures the product picture. They combine through a geometric mean:
Total = √(Quantitative × Strategic)
Neither side can compensate for the other. A cheap stock with no moat fails. A great business at a terrible price fails. Both must hold. The rest of this post walks through each side and the decisions behind the numbers.
The quantitative engine
Four dimensions, each scored one to five, combined as a weighted average.
- Valuation (30%): PEG ratio (price-to-earnings divided by growth rate) and analyst upside. Are you overpaying relative to growth?
- Quality (30%): ROIC (return on invested capital, how much profit per dollar invested), gross margin, and a net cash bonus. Does the business generate real returns?
- Growth (20%): three-year revenue CAGR (compound annual growth rate) and forward EPS (earnings per share) growth. Is the company actually expanding?
- Risk (20%): beta (how much a stock moves relative to the market) and debt-to-equity. How leveraged and volatile is it?
The thresholds:
| Metric | 5 | 4 | 3 | 2 | 1 |
|---|---|---|---|---|---|
| PEG ratio | < 1.0 | 1.0 - 1.5 | 1.5 - 2.5 | 2.5 - 3.5 | > 3.5 |
| Analyst upside | > 30% | 15 - 30% | 10 - 15% | 0 - 10% | < 0% |
| ROIC | > 25% | 15 - 25% | 10 - 15% | 5 - 10% | < 5% |
| Gross margin | > 50% | 40 - 50% | 35 - 40% | 30 - 35% | < 30% |
| Revenue CAGR (3yr) | > 20% | 10 - 20% | 5 - 10% | 0 - 5% | declining |
| EPS forward growth | > 25% | 15 - 25% | 10 - 15% | 0 - 10% | declining |
| Beta | 0.7 - 1.0 | 1.0 - 1.2 | 1.2 - 1.5 | 1.5 - 2.0 | > 2.0 |
| Debt-to-equity | < 0.3 | 0.3 - 0.7 | 0.7 - 1.0 | 1.0 - 1.5 | > 1.5 |
A few decisions worth explaining.
- PEG over forward P/E. A company growing twenty percent at 25x earnings gets a PEG of 1.25, which scores a four. Forward P/E alone would penalize it for looking expensive.
- Debt-to-equity moved from Quality to Risk. It used to live alongside ROIC, but that double-counted leverage. I replaced it with a simple binary: if the company has more cash than debt, Quality gets a half-point bonus.
- Gross margin over free cash flow margin. Gross margin is independent of capital structure. FCF margin made asset-light businesses look artificially better.
The strategic side
Two dimensions, equal weight.
- Problem. How severe and durable is the issue this company solves? Is it must-have or nice-to-have? What happens if nobody solves it? Is regulation mandating a solution?
- Defensibility. Why can someone with more resources not just take the market? I lean on Hamilton Helmer's 7 Powers and add a product lens: how painful is it to migrate away, does the user live inside the application all day, does the product get smarter with more data, is there a free alternative that solves eighty percent of the problem.
This side cannot be automated. It requires reading earnings calls, SEC filings, and analyst reports. It is the slowest part of the process, roughly thirty to sixty minutes per company, and the part where conviction actually forms.
How they combine
The geometric mean penalizes imbalance. A stock scoring five on one side and one on the other gets a 2.24, not a 3.0. It does not enter the portfolio.
| Score | Classification | Position size |
|---|---|---|
| 4.5 or above | Exceptional | 15 - 25% |
| 3.5 to 4.4 | Strong | 8 - 15% |
| 3.0 to 3.4 | Acceptable | 3 - 8% |
| Below 3.0 | Does not enter | N/A |
Position sizes are not arbitrary. Base weight comes from the score total, adjusted by beta, with a cap at twenty-five percent. If two positions have weekly correlation above 0.7 over a three-year window, only the higher-scored one stays. Maximum thirty-five percent in any single theme, minimum five positions.
Before any of this runs, an ethical filter removes fossil fuels, weapons, tobacco, gambling, and private prisons. Binary gate, no scoring needed.
The framework in action
Two real examples from my evaluations.
MSCI
| Score | Detail | |
|---|---|---|
| Valuation | 4 / 5 | Revenue $3.1B, up 9.75% |
| Quality | 5 / 5 | 96% recurring revenue, strong margins |
| Growth | 4 / 5 | 11th straight year of double-digit EPS growth |
| Risk | 3 / 5 | High debt levels, fees tied to AUM |
| Quantitative | 4.10 | |
| Problem | 5 / 5 | Trillions benchmarked to its indexes, regulation mandates their use |
| Defensibility | 5 / 5 | Switching would be like changing the metric system |
| Strategic | 5.00 | |
| Total | 4.53 (Exceptional) |
Decent numbers, extraordinary moat. The qualitative side reveals what the financials alone cannot capture.
YOU (Clear Secure)
| Score | Detail | |
|---|---|---|
| Valuation | 5 / 5 | Analyst upside +32% |
| Quality | 5 / 5 | ROE 76%, gross margin 86%, net cash |
| Growth | 5 / 5 | Revenue up 17% YoY, $343M FCF |
| Risk | 4 / 5 | Beta 1.10, retention declining |
| Quantitative | 4.80 | |
| Problem | 3 / 5 | Convenience, not necessity. TSA PreCheck solves 70% at a fraction of the price |
| Defensibility | 3 / 5 | Zero switching cost, no workflow lock-in |
| Strategic | 3.00 | |
| Total | 3.79 (Strong) |
Excellent financials hiding a fragile thesis. A full tier below what the numbers alone would suggest.
What the framework favors
This is not a neutral screener. By design, it rewards businesses with high returns on capital, strong moats, and durable problems. That means it naturally gravitates toward quality compounders: companies that reinvest at high rates behind defensible advantages. It also has a structural bias toward asset-light models, since gross margin and ROIC tend to be higher when there is less physical infrastructure. Vertical SaaS companies score well through the PM lens. Capital-intensive businesses, turnarounds, and deep value plays are structurally disadvantaged. That is intentional. I want conviction, and these are the businesses where I can build it.
What I don't know yet
This is version one with real money behind it. I am monitoring quantitative-only rankings alongside the combined score to see whether the strategic side actually adds alpha or just adds work. The weights might be wrong. Some thresholds are probably too generous, others too strict. I will find out as I run this through more market cycles.
What I do know is that the process itself has been valuable. Forcing myself to articulate why a business matters, what its moat actually is, whether the problem it solves is real and durable. That is where my conviction comes from. Not from the final number, but from understanding what the number represents.