Home / Financial Tools / Piotroski F-Score Fundamental Strength Screener

Graduate-Level Modeling · Fundamental Analysis

Piotroski F-Score Fundamental Strength Screener

Nine simple yes-or-no accounting questions, no valuation multiple required, that Piotroski showed meaningfully separated future winners from losers among cheap, unglamorous value stocks.

How To Use This Model

Reading This Tool

Toggle each of the nine signals based on the company's year-over-year financials.

Each "yes" adds one point across three categories: profitability, leverage/liquidity, and operating efficiency. The total score out of 9 is the F-Score.

The Nine Piotroski Signals

Each signal is a strict year-over-year comparison against the same figure one year prior, drawn directly from the balance sheet, income statement, and cash flow statement.

Composite F-Score

-

Piotroski F-Score (Out Of 9)

0

Profitability (Of 4)

-

Leverage/Liquidity (Of 3)

-

Efficiency (Of 2)

-

Score By Category

-

-

Which Category Is Actually Weakest

-

Why This Was Originally Built For Value Stocks Specifically

Piotroski designed this for high book-to-market (value) stocks specifically, where the market has already priced in pessimism. The F-Score's job is separating the genuinely improving businesses from the ones the market is right to avoid, within that already-cheap universe. Applying it to expensive growth stocks is a meaningfully different exercise the original research didn't test.

The "No New Shares" Signal, Explained

This specifically checks for dilutive share issuance, a proxy for whether the company can fund itself internally versus needing to continually raise external equity, often a signal of financial weakness or negative free cash flow when it recurs.

Fundamental Screening

The Nine Signals, By Category

Profitability: ROA>0, CFO>0, ΔROA>0, CFO>NetIncome
Leverage/Liquidity: ΔLTDebtRatio<0, ΔCurrentRatio>0, No New Shares
Efficiency: ΔGrossMargin>0, ΔAssetTurnover>0
F-Score = Sum of all nine binary signals (0 to 9)

Each signal is scored 1 or 0 based on a strict year-over-year comparison, no partial credit or magnitude weighting, deliberately keeping the model simple and resistant to overfitting on any single ratio's threshold.

When To Actually Use This Model

  • Screening a universe of high book-to-market (statistically cheap) stocks to separate improving from deteriorating fundamentals.
  • Teaching fundamental analysis and financial statement-based stock screening in an investments or equity analysis course.
  • A quick, standardized quality check before deeper due diligence on a specific value investment candidate.
  • Building or back-testing a systematic value-with-quality equity strategy.

Key Assumptions & Limitations

  • Originally validated specifically on high book-to-market stocks; less tested outside that context.
  • Binary scoring ignores magnitude, a stock that barely improved ROA scores identically to one whose ROA doubled.
  • Requires two full years of comparable financial statements, unusable for newly listed companies.
  • Does not directly address earnings manipulation risk, pairing with a tool like the Beneish M-Score adds that dimension.

Foundational Reference

Piotroski, J. D. (2000). Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers. Journal of Accounting Research, 38, 1-41.

Want the earnings manipulation cross-check too?