Piotroski F-Score vs Altman Z-Score: Quality Signals vs Distress Risk
Boeing’s fiscal 2025 accounts produce two results that appear difficult to reconcile.
Its Piotroski F-Score is 6/9, a mixed result with six favorable tests spanning current-year conditions and year-over-year change. Using the same fiscal-year accounts and a July 22, 2026 market-price input, its Altman Z-Score is approximately 1.51, inside the StockGeniuses High Distress Risk zone.
Did Boeing’s financial condition improve, or did it remain structurally stressed?
Both statements can be true.
The Piotroski F-Score and Altman Z-Score sit in the same broad financial-health family, but they do not measure the same dimension. Piotroski combines several current-year health checks with comparisons against the previous fiscal year, so it emphasizes financial trajectory. Altman asks whether the latest financial and market profile falls into a lower- or higher-distress zone under a specific formula.
One emphasizes direction. The other classifies condition.
That distinction is the foundation of a useful Piotroski F-Score vs Altman Z-Score comparison. It also explains why model disagreement should open an investigation rather than force an investor to choose a winner.
The two scores begin with different questions
Joseph Piotroski introduced the F-Score in his 2000 paper, Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers. The original research used nine financial-statement signals to distinguish stronger and weaker firms inside a high book-to-market population.
The model’s construction is directional. Several conditions compare the current fiscal year with the previous one: return on assets, leverage, liquidity, gross margin, and asset turnover. Other conditions ask whether current profitability, cash flow, earnings quality, and equity funding clear binary tests.
Edward Altman’s original 1968 model came from a different problem. Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy combined five weighted ratios to separate bankrupt and non-bankrupt manufacturing-company profiles in its historical sample.
The original public-company Z-Score is primarily a level-based classification. It uses latest-period working capital, retained earnings, EBIT, liabilities, revenue, and assets, then adds current market value of equity. Altman later developed other variants for different company populations, as he discussed in a CFA Institute interview.
Both models belong in the Financial Health & Risk family within the broader comparison of nine stock analysis models. Their proximity does not make them interchangeable.
| Dimension | Piotroski F-Score | Original Altman Z-Score |
|---|---|---|
| Core question | Are selected annual conditions favorable, and are key metrics improving? | What structural distress zone does the latest profile occupy? |
| Data window | Two consecutive completed fiscal years | Latest completed fiscal year plus T-1 adjusted close |
| Structure | Nine unweighted binary tests | Five continuous ratios with different weights |
| Output | Integer from 0 to 9 | Continuous Z-Score and risk zone |
| StockGeniuses labels | 7-9 Strong, 4-6 Mixed, 0-3 Weak/Deteriorating | Above 2.99 Low Distress Risk, 1.81-2.99 Grey Zone, below 1.81 High Distress Risk |
| Market price used | No | Yes, through market value of equity |
| Important model fit | Complete comparable annual statements | Original form is most defensible for public manufacturers |
| What it does not output | Intrinsic value, expected return, timing, or recommendation | Bankruptcy certainty, intrinsic value, expected return, timing, or recommendation |
This comparison follows a general rule for reading a stock analysis model: compare the question, eligible population, input period, formula, and output before comparing the headline numbers.
Direction does not reveal the starting level
Suppose a company moves from a severe annual loss to a small profit, generates positive operating cash flow, and improves its margins. Piotroski can correctly record those changes as positive signals.
The same company may still carry high liabilities, thin working-capital support, accumulated financial strain, and a market value that is modest relative to its obligations. Altman can correctly classify that latest profile in a high-distress zone.
There is no contradiction. Improvement answers “Which way did selected indicators move?” Structural condition answers “Where does the current profile stand under this model?”
The reverse can also occur. A financially strong company may remain comfortably above Altman’s low-distress threshold while several annual indicators weaken. The deterioration deserves attention, but it does not instantly erase the capacity accumulated before that year.
This is why phrases such as “strong company” and “safe stock” are too broad for either output. A high F-Score is not a complete business-quality judgment. A high Z-Score does not make a security safe in every relevant sense. The labels must remain attached to the narrow evidence each formula processes.
Boeing provides a controlled same-company comparison
The Boeing example uses the company’s fiscal 2025 Form 10-K. Piotroski compares fiscal 2025 with fiscal 2024. Altman uses fiscal 2025 financial statements and the same July 22, 2026 adjusted close already audited in the complete Boeing Altman Z-Score example.
The Altman analysis snapshot is dated July 23, 2026. Its market input is the July 22 adjusted close of $208.65, combined with 784.70 million fiscal-year shares; those values were cross-checked through AlphaQuery’s Boeing financial data. Reusing the snapshot keeps the company, fiscal period, formula, share count, and market-price date explicit. It avoids comparing a newly calculated Piotroski result with a silently refreshed Altman result.
All financial-statement values below are in millions of U.S. dollars except shares. The calculations use unrounded values internally.
Boeing’s nine Piotroski tests
The StockGeniuses Piotroski implementation assigns one point for each strict pass. It does not reweight a signal because it appears more economically important, and it does not calculate a partial score when a required input is missing.
| Piotroski condition | FY2025 evidence | FY2024 evidence | Result |
|---|---|---|---|
| Net income is positive | Net earnings 2,238 | Not required for this test | Pass |
| Cash from operations is positive | 1,065 | Not required for this test | Pass |
| Return on assets improved | 1.33% | -7.57% | Pass |
| Cash from operations exceeds net income | 1,065 < 2,238 | Not required for this test | Fail |
| Long-term debt / total assets declined | 27.13% | 33.63% | Pass |
| Current ratio improved | 1.188 | 1.319 | Fail |
| Shares outstanding did not increase | 784.70 million | 749.22 million | Fail |
| Gross margin improved | 4.79% | -2.99% | Pass |
| Asset turnover improved | 0.532 | 0.425 | Pass |
The six passes produce:
F-Score = 6 / 9
Under the locked StockGeniuses labels, 6 is Mixed. The result contains meaningful improvement, but it is not an all-clear signal.
Profitability turned positive. Operating cash flow turned positive. Return on assets, gross margin, and asset turnover improved from a difficult comparison year. Long-term debt also declined relative to total assets.
Three tests preserve the tension. Operating cash flow remained below net earnings, the current ratio weakened, and the year-end share count increased.
The matched Altman result
The original public-manufacturer formula used by StockGeniuses is:
Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5
For the dated Boeing snapshot:
| Altman component | Boeing input or ratio |
|---|---|
Working capital / total assets (X1) | 0.1209260855 |
Retained earnings / total assets (X2) | 0.1025470324 |
EBIT / total assets (X3) | 0.0254465480 |
Market value of equity / total liabilities (X4) | 1.0058340501 |
Revenue / total assets (X5) | 0.5317740066 |
| Final Z-Score | 1.5079251930 |
Displayed to two decimals, the result is 1.51. Because it is below 1.81, StockGeniuses classifies the snapshot as High Distress Risk.
That label does not say Boeing will enter bankruptcy. It says the selected original-form inputs place the dated profile below the model’s high-distress boundary. It also does not cancel the six Piotroski passes. The latest structural level and the annual direction remain separate observations.
The disagreement becomes useful when the scores are reopened
Displaying 6 beside 1.51 is not enough. The value comes from tracing the two outputs back to the facts that produced them.
A leverage pass can conceal a maturity shift
Piotroski’s leverage condition compares long-term debt divided by total assets:
- FY2025:
45,637 / 168,235 = 27.13% - FY2024:
52,586 / 156,363 = 33.63%
The ratio declined, so the condition correctly passes.
But Boeing’s debt note shows a more complicated picture. Current debt rose from $1.278 billion to $8.461 billion, while total debt moved from $53.864 billion to $54.098 billion. Some of the apparent long-term-debt improvement reflects debt moving closer to maturity, and the expanding asset denominator also helps the ratio.
The binary pass is not wrong. The broad conclusion “Boeing reduced its debt burden” would be too strong.
This is why core metrics must remain visible around model outputs. Long-term debt, current debt, total debt, assets, maturities, and refinancing needs answer related but different questions.
Positive earnings did not receive an accrual-quality pass
Boeing reported fiscal 2025 net earnings of $2.238 billion and cash from operations of $1.065 billion.
Positive net earnings earn one point. Positive operating cash flow earns another. Return on assets improved sharply from the prior-year loss, earning a third profitability point.
However, cash from operations did not exceed net income. The accrual-quality condition therefore fails.
That failure is particularly informative because Boeing reported $9.672 billion of net gains on dispositions, including a large Digital Aviation Solutions divestiture gain. The Piotroski formula does not normalize reported net income for this event. Instead, its cash-versus-income test raises a separate warning: the accounting profit was not matched by equal operating cash generation.
The test does not prove that earnings were low quality. It tells the reader where reconciliation is required.
The same disposition gain also enters Altman’s X3 through Boeing’s reported earnings from operations. One unusual event can therefore affect Piotroski’s positive-income, ROA, and cash-quality tests while also lifting an Altman component. The models are complementary, but they are not independent data sources. Agreement or disagreement still has to be traced back to the accounting inputs they share.
Improvement followed an unusually weak comparison year
Revenue rose from $66.517 billion to $89.463 billion. Gross margin moved from approximately -2.99% to 4.79%, and asset turnover rose from 0.425 to 0.532.
Those are valid year-over-year improvements. They also began from fiscal 2024, when Boeing reported an $11.829 billion net loss and negative gross margin under the inputs used here.
One improving year after a severe decline is not the same as a durable multi-year recovery. A separate historical performance review is needed to see whether the direction persists, stalls, or reverses.
The Altman score brings accumulated condition and market confidence back into view
Piotroski does not use retained earnings, total liabilities, or market value of equity. Altman does.
That gives the Z-Score information the F-Score cannot preserve. Its retained-earnings ratio carries part of the company’s accumulated history. Its market-equity ratio compares market value with total liabilities. Its working-capital and EBIT ratios assess current structural support relative to the asset base.
The tradeoff runs both ways. Altman’s original formula does not directly ask whether the current ratio, margin, or return on assets improved from the prior year. It can classify the latest profile without capturing the same reversal evidence.
Used together, the models add dimensions. They should not be averaged into a fictional master number.
The two totals cannot be converted into votes
An F-Score point and a Z-Score decimal do not share a common unit.
Piotroski’s nine conditions are unweighted pass/fail observations. Moving from 5 to 6 means one additional condition passed, but it does not reveal which condition, the size of the change, or whether the company crossed the threshold narrowly.
Altman’s output is a weighted linear combination. Moving from 1.51 to 1.61 could result from changes in operating earnings, working capital, market capitalization, or several components at once. It still does not mean the company became a fixed percentage safer.
Converting both results to percentages, averaging their labels, or counting them as equal bullish and bearish votes would create precision that neither model supplies. The defensible synthesis remains verbal and evidence-specific: selected annual conditions improved, while the dated structural profile remained inside a high-distress zone.
Four combinations are possible
The two models create a more useful map when direction and condition remain on separate axes.
| Directional evidence | Structural distress evidence | Careful interpretation |
|---|---|---|
| Stronger Piotroski pattern | Lower Altman distress | Selected fundamentals improved while the latest structural profile remains comparatively stronger under Altman. Verify durability and model fit. |
| Stronger Piotroski pattern | Higher Altman distress | Improvement may be underway from a weak base, but structural strain remains. Boeing’s dated example illustrates this combination. |
| Weaker Piotroski pattern | Lower Altman distress | Annual fundamentals deteriorated, but accumulated capacity may still provide a cushion. Investigate whether the decline is temporary or the start of a trend. |
| Weaker Piotroski pattern | Higher Altman distress | Direction and structural condition both raise concern. The result still requires input, industry, and accounting review rather than an automatic investment conclusion. |
These are analytical states, not portfolio instructions.
Even the first combination does not establish attractive valuation, durable competitive advantage, or favorable expected return. The last combination does not establish certain failure or prove that the market price already reflects too little risk.
The matrix exists to make the next research question clearer.
When to use Piotroski, Altman, both, or neither
Use Piotroski when direction is the main question
Piotroski is useful when two comparable completed fiscal years are available and the investor wants a consistent review of profitability, financial structure, funding, margin, and asset-efficiency changes.
Its binary construction makes the result easy to audit. That simplicity also discards magnitude. A tiny improvement receives the same point as a large improvement, while a narrow miss receives zero.
Read the complete Piotroski F-Score guide when the nine conditions, exact input definitions, or score-band interpretation require closer review.
Use the original Altman model when structural distress is the main question
The original Altman Z-Score is most defensible when the company is a publicly traded manufacturer and complete, appropriately timed inputs are available.
It is useful for examining the combination of liquidity, accumulated profitability, operating earnings, market equity support, and asset turnover. Its weighted continuous output preserves distance better than a binary pass count, but the result remains sensitive to formula version, market-price date, industry fit, and accounting inputs.
Use both when the company fits both contracts
Both models add value when an investor needs to know:
- whether selected annual financial signals are moving in a stronger or weaker direction; and
- whether the latest profile still occupies a lower- or higher-distress zone.
The correct combination is not “Altman first, Piotroski second” for every investor. Nor is it a rule that one threshold automatically excludes a stock.
Use each result for its own question. Reopen the inputs. Then investigate the disagreement.
Use neither when model fit or data integrity fails
StockGeniuses does not force partial outputs from incomplete inputs. If either model lacks required data, that result becomes Not Meaningful.
Financial institutions are a particularly important model-fit problem. Their regulated capital, deposits, and balance-sheet structure do not map cleanly to the original industrial Altman formula. Major acquisitions, divestitures, recapitalizations, and accounting changes can also weaken period comparability for Piotroski.
A calculable number is not automatically a meaningful number.
Both models leave major questions outside the calculation
Piotroski and Altman can organize financial evidence, but neither model directly answers:
- what the business is worth;
- whether the stock price offers a margin of safety;
- when debt matures or what refinancing terms may apply;
- whether interest coverage is adequate under a downturn;
- how concentrated customers, suppliers, programs, or segments are;
- whether an apparent earnings recovery is recurring;
- whether management can execute an operational plan;
- whether competitive advantage is strengthening;
- what future cash flows or returns will be; or
- whether the investor should buy, sell, or hold.
Those omissions are not defects to hide. They are the boundary that makes each model interpretable.
The broader financial strength and risk signals guide returns leverage, liquidity, coverage, refinancing pressure, and cash-flow resilience to their original units. That evidence can explain why a composite score moved and reveal risks the score never contained.
StockGeniuses preserves disagreement by design
Inside StockGeniuses, Piotroski and Altman are separate models within Financial Health & Risk Assessment. Each has its own model contract, output, interpretation, and eligibility.
That architecture reflects a deliberate principle: models are nonredundant. They can confirm one another, conflict, or become Not Meaningful for different reasons.
An improving Piotroski result should not be allowed to erase a high-distress Altman classification. A lower-distress Altman result should not silence a deteriorating Piotroski pattern. Presenting both makes the evidence more honest.
The product-level value is not a louder verdict. It is a clearer account of why different methods disagree and which inputs deserve attention next.
The stronger answer is two bounded answers
For Boeing’s dated fiscal 2025 example, the defensible conclusion is limited but useful.
The Piotroski F-Score is 6/9, reflecting a mixed pattern with meaningful year-over-year improvement and three unresolved tests. The matched original-form Altman Z-Score is approximately 1.51, placing the snapshot in the StockGeniuses High Distress Risk zone.
Together, the models say that six selected tests passed, including several year-over-year improvements, while structural distress evidence remained elevated under the Altman formula.
They do not say that Boeing is cheap, expensive, safe, doomed, or suitable for an investor. They identify a recovery-versus-condition tension that deserves deeper work on cash conversion, debt maturities, liquidity, recurring operating economics, and historical persistence.
That is how a model comparison should improve a systematic stock analysis process: not by manufacturing one answer, but by making the boundaries and next questions harder to miss.
This article is educational and does not provide investment advice or a recommendation regarding The Boeing Company or any other security.