Valuation

Piotroski F-Score

A 9-point scoring system evaluating a company's financial strength across profitability, leverage, and operating efficiency.

The Piotroski F-Score was developed by Stanford accounting professor Joseph Piotroski in 2000. It is a composite score from 0 to 9 that assess a company's financial health across three categories: profitability, leverage/liquidity, and operating efficiency. Each criterion is binary — one point if met, zero if not.

Profitability criteria include: positive return on assets (ROA), positive operating cash flow, year-over-year improvement in ROA, and cash flow from operations exceeding net income. Leverage criteria: declining long-term debt ratio, improving current ratio, and no new share issuance (which would signal dilution). Efficiency criteria: improving gross margin and improving asset turnover.

A score of 7–9 is considered 'High Quality' — strong financial health. 5–6 is 'Solid.' Below 5 is 'Weak' and may indicate financial distress or operational deterioration.

Important caveat on StressTest.pro: The Piotroski score is a proxy model applied to trailing-twelve-month financial statement data. It was designed for value stocks and may not be meaningful for mega-cap software companies with non-traditional capital structures (e.g. Microsoft, Google) where classic accounting ratios appear anomalous.

Frequently Asked Questions

Why does a huge company like Microsoft have a low Piotroski score?

The Piotroski model was designed for traditional capital-intensive businesses. Software companies with enormous cash returns to shareholders (buybacks) can score poorly on 'new share issuance' and debt metrics even when fundamentally healthy. Always interpret scores in the context of the business model.

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Disclaimer

The information provided by StressTest.pro is for educational and informational purposes only and does not constitute financial advice. Investment involves risk, including possible loss of principal. Past performance is not indicative of future results. Calculations are based on historical data and statistical approximations.