Stock sectors where top quality is almost unachievable
2026-06-22 · By Lubin Danilo, founder of Lubin Investment
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Out of 5,000+ companies analyzed, fewer than 60 earn the maximum quality score. Banks, energy, and large-scale retail are almost entirely absent: massive leverage, razor-thin margins, and capex that consumes nearly all cash flow. This is not a value judgment on these sectors, it is a structural filter.
A list of fewer than 60 companies out of 5,000
The Lubin screener reviews more than 5,000 listed companies across ten fundamental quality criteria. A company that passes all of these earns the maximum score. The result: fewer than 60 manage it, less than 1.2% of the analyzed universe.
Why banks almost always fail
A bank operates with extreme leverage. To lend 100 euros, it owns only 8 to 12 in equity. That debt-to-equity ratio would be considered catastrophic in any other sector. A bank's net interest margin is also inherently unpredictable, it depends on central bank decisions, the yield curve, the credit cycle. Over five years, earnings consistency is nearly impossible to satisfy.
Why oil and gas energy is structurally incompatible
Oil majors and gas producers face revenues that depend on a price they do not control. The barrel can rise 40% one year and fall 60% the next. Capex absorbs 70 to 90% of operating cash flow. Energy services companies like SLB and Cactus (WHD) are different, they sell equipment and services, with more stable margins, and a few do reach the top score.
Why large-scale retail does not pass the filter
Grocery retail reports net margins of 1 to 3%. Capex is enormous. Amazon forced all traditional distributors to invest massively in logistics without being able to raise prices proportionately. Exception: companies like GoDaddy (GDDY) classified in tech retail actually run a SaaS model with near-software margins.
| Sector | Examples | Main reason for exclusion | Possible exceptions |
|---|---|---|---|
| Banks | JPMorgan, BNP Paribas | Massive leverage, earnings not converted into real FCF | Rare, never structurally |
| Oil & gas energy | ExxonMobil, TotalEnergies | Unpredictable commodity prices, capex 70-90% of operating cash | Energy services: SLB, WHD |
| Large-scale retail | Walmart, Carrefour | Net margins 1-3%, enormous logistics capex, Amazon pricing pressure | Tech retail with recurring revenue: GDDY |
What this means for your portfolio
The absence of these sectors from the top-score list does not mean they should be avoided outright. Banks can produce excellent returns in a rising-rate environment. Oil majors distribute very high dividends at cycle peaks. The Lubin method focuses on durable structural quality regardless of the economic cycle.
FAQ
Why do banks carry so much debt on their balance sheet?
The banking model is structurally built on leverage: a bank borrows to lend. A debt-to-equity ratio of 8 or 10 to 1 is the regulatory norm.
Are oil companies making bad investments?
Not necessarily, but their business is exposed to a price they do not control. Consistency over five years is structurally very difficult to achieve.
Why does Amazon weaken traditional large-scale retail?
Amazon imposed fast delivery and competitive prices as the new market standard. Traditional distributors had to invest massively without being able to pass these costs on to customers.
Is GoDaddy really classified as retail?
GoDaddy (GDDY) is often categorized in tech retail by financial databases, but its recurring revenue model, web hosting, domain names, SME SaaS, is fundamentally different from grocery retail.
Could the screener be adapted to better capture banks?
The screener's criteria apply poorly to financial intermediaries by construction. Adapting it to banks would require an entirely different framework. This is not investment advice.
Related reading
- Electric utilities, solar stocks: why they stall
- Unexpected sectors: HST, CWCO, OMAB, IMAX in the screener
- European quality stocks: which ones are actually cheap?
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About the author
Written by Lubin Danilo, founder of Lubin Investment. A self-taught individual investor, I find fundamental analysis fascinating, and it has delivered excellent results. For three years now, my performance has beaten the S&P 500. But analyzing every stock took too much time: sites with incomplete data, calculation methods and criteria never aligned with mine. And spotting the best stocks was just as time-consuming, even with my own well-defined checklist. So I put my software development background to work to build this software, base my investment strategy on its results, and share it with people who share the same passion as me. It judges a company's quality and its price separately, using criteria drawn from the financial literature (Warren Buffett, Michael Mauboussin, Aswath Damodaran).