Open any finance site and you drown in absolute numbers. A price-to-earnings ratio of 30. A debt-to-capital of 45%. Revenue growth of 8%. Each is precise — and each is, on its own, almost meaningless. Is 30 expensive? For a utility, wildly. For a software company compounding revenue at 20% a year, maybe cheap.
The problem is that absolute metrics carry no context. Industries have structurally different economics: software runs gross margins a steel mill will never see; banks are leveraged by design; insurers hold float that distorts every balance-sheet ratio. Comparing a pharma company’s P/E with a miner’s tells you about the industries, not the companies.
Rank against the companies that compete for the same capital
Obermatt takes a different route: every metric is converted into a rank from 1 to 100 against the company’s true peers — companies of comparable industry and size, the ones an investor would actually weigh against each other. A value rank of 80 doesn’t say “the P/E is X”; it says “this stock is priced more attractively than 80% of the companies it actually competes with for your money.”
- Ranks are comparable everywhere. An 80 in Swiss pharma means the same thing as an 80 in US semiconductors: top fifth of its peer group. One scale, every industry, every country.
- Ranks absorb industry economics. Banks are ranked with bank-specific safety measures (Basel-III liquidity, tier-1 capital) against other banks — not punished for not looking like a software company.
- Ranks resist accounting noise. A rank moves only when a company shifts relative to its peers — sector-wide shocks that hit everyone equally largely cancel out.
None of this makes ranks a buy signal by themselves. What they give you is honest context — the starting point absolute numbers pretend to be. Where a screen full of ratios asks you to be an analyst, a single number from 1 to 100 asks you a much better question: compared with the alternatives, where does this stock really stand?