Classic investor frameworks · Screening and validation

Piotroski · F-Score

Uses nine public financial signals to separate improving low-valuation stocks from potential value traps.

Guide level: Practical
Output: Screening and validation

What question does this model answer?Do nine public accounting signals show improving financial quality or a potential value trap?

Core formula

F-Score = sum of nine binary profitability, leverage/liquidity and efficiency signals

How to interpret it

Uses nine public financial signals to separate improving low-valuation stocks from potential value traps.

The output should be read as a scenario or decision aid, not as a guaranteed price target. Compare it with at least one method based on different economic assumptions.

Practical workflow

Normalize the latest public financial and operating data.
Choose assumptions that match the company's economics and accounting structure.
Calculate conservative, base and optimistic cases where the method permits.
Compare the result with market pricing and an independent valuation method.
Document the assumptions that drive the largest changes in value.

Key limitation

It is a screening signal, not a fair-value estimate, and accounting events can distort individual tests.

How Stockinsky uses it

Stockinsky uses this framework only when the company type and available data support it. Professional valuations expose assumptions, sources and warnings instead of presenting false precision.

References

Primary reference 1

Valuation outputs depend on public data and explicit assumptions. They cannot guarantee forecast accuracy and are not investment advice.