The Altman Z-Score was developed in 1968 and has since predicted corporate bankruptcy with approximately 80–90% accuracy in the two years before failure. For stock screeners, it serves as a quantitative quality filter — a way to remove financially distressed companies from a candidate list before applying valuation criteria.
Last updated: June 2026.
What the Altman Z-Score is
Edward Altman was a finance professor at NYU who in 1968 published a model predicting corporate bankruptcy using five financial ratios. The original model was built on US manufacturing companies. Over decades, Altman and others extended it to other sectors and geographies, including a modified version for non-manufacturing companies that applies better to European equities.
The original Z-Score formula:
Z = 1.2(X1) + 1.4(X2) + 3.3(X3) + 0.6(X4) + 1.0(X5)
Where:
- X1 = Working Capital / Total Assets (liquidity)
- X2 = Retained Earnings / Total Assets (leverage and profitability history)
- X3 = EBIT / Total Assets (profitability)
- X4 = Market Value of Equity / Book Value of Total Liabilities (leverage and market valuation)
- X5 = Revenue / Total Assets (asset utilisation)
Interpretation:
- Z > 2.99: Safe zone — low probability of financial distress
- 1.81 < Z < 2.99: Grey zone — some risk, monitor closely
- Z < 1.81: Distress zone — high probability of financial distress within two years
The Z'-Score: Altman's modified model for European companies
The original Z-Score was calibrated on US manufacturing companies. For non-manufacturing businesses (including most European listed companies), Altman developed the Z'-Score:
Z' = 0.717(X1) + 0.847(X2) + 3.107(X3) + 0.420(X4) + 0.998(X5)
Where X4 in this version uses Book Value of equity (rather than market value) divided by total liabilities — reducing the model's sensitivity to stock price fluctuations.
Interpretation for Z':
- Z' > 2.9: Safe zone
- 1.23 < Z' < 2.9: Grey zone
- Z' < 1.23: Distress zone
For European small caps with limited analyst coverage and potentially volatile prices, the Z'-Score is generally more appropriate than the original Z.
Why the Z-Score matters for European stock screeners
Filtering out financial landmines
The most practical use of the Z-Score in a screening context is as a quality gate: exclude companies in the distress zone before applying valuation filters.
A stock trading at P/E 8 and EV/EBITDA 5 looks like a value stock. But if its Z-Score is 0.9, the cheap valuation reflects genuine distress risk — it's not undervalued, it's potentially headed for bankruptcy. Without a financial health filter, value screens can fill up with companies that look cheap because they're broken.
Small cap risk management
European small caps — particularly in Italy, Spain, and Eastern Europe — carry higher financial distress rates than large caps. The analyst coverage that would flag deteriorating balance sheets for large companies doesn't exist for €100M companies. The Z-Score provides a quantitative early warning that doesn't depend on analyst coverage.
Cycle-proofing quality screens
In economic downturns, the companies that survive and emerge with stronger competitive positions are those that entered with financial strength. Screens built with Z-Score guards tend to hold up better in bear markets because they systematically avoid the companies most vulnerable to economic stress.
How to use Z-Score in stock screening
Most screeners don't expose the Z-Score directly as a filter, but you can approximate it with the component metrics:
Component proxy filters
X1 — Working Capital / Total Assets (liquidity): → Screen for: Current Ratio > 1.5, or Working Capital Positive
X2 — Retained Earnings / Total Assets (accumulated profitability): → Screen for: Retained Earnings > 0 (positive, indicating the company has historically been profitable)
X3 — EBIT / Total Assets (return on assets): → Screen for: EBIT margin > 5%, or ROA > 3%
X4 — Equity Value / Liabilities (leverage): → Screen for: Debt/Equity < 1.0, or Total Liabilities / Total Assets < 0.6
X5 — Revenue / Total Assets (asset efficiency): → Screen for: Asset Turnover > 0.5
Running all five proxies simultaneously screens out most distress-zone companies effectively.
Direct Z-Score filter (where available)
Some screeners provide Z-Score as a calculated field. Where available:
- Z-Score > 2.5: Strong financial health (within safe zone)
- Z-Score > 2.0: Acceptable health (upper grey zone)
- Z-Score < 1.5: Flag for closer inspection before investing
What Z-Score thresholds mean by sector
The Z-Score was calibrated on industrial companies. Different sectors have different baseline Z-Score expectations:
| Sector | Typical Z-Score range | Notes |
|---|---|---|
| Technology (asset-light) | 3–8+ | High asset turnover and margins produce high scores |
| Consumer discretionary | 2–5 | Varies significantly by business model |
| Industrials/Manufacturing | 1.5–4 | Original calibration — scores are most reliable here |
| Retail | 1.5–3.5 | High payables (which reduce working capital) compress scores |
| Healthcare | 2.5–6 | Asset-light models score well; pharma can be misleading |
| Energy/Materials | 1–3 | Cyclical revenues and high asset bases compress scores |
| Banks/Financials | Not applicable | Banks require entirely different models (use CET1, leverage ratio) |
| Real estate | Not applicable | Asset-heavy structure distorts Z-Score; use LTV and ICR instead |
Important: Never apply Z-Score to financial companies (banks, insurance, diversified financials) or to real estate investment trusts. The model wasn't designed for these sectors and produces meaningless results.
Case study: the Z-Score as an early warning
A practical illustration of how Z-Score would have helped:
Retail company — declining Z-Score:
- Year 1: Z' = 2.3 (grey zone — some risk)
- Year 2: Z' = 1.8 (grey zone — worsening)
- Year 3: Z' = 1.1 (distress zone — serious risk)
- Year 4: Company files for insolvency protection
The Z-Score was signalling deterioration three years before the failure. A screener that filters for Z' > 1.5 would have excluded this company at Year 3, before the distress became obvious in the stock price.
Z-Score limitations to know
Not a standalone sell signal: A low Z-Score means risk, not certainty of failure. Companies in the grey zone often recover. The score is a filter, not a verdict.
Backward-looking: The Z-Score uses historical balance sheet data. A company can deteriorate rapidly in ways that a balance sheet from 6 months ago won't capture.
Seasonal distortions: Companies with seasonal revenue cycles show very different working capital positions depending on when the balance sheet is taken. A retailer's December balance sheet looks much better than its August one.
Doesn't capture off-balance-sheet liabilities: Lease obligations (pre-IFRS 16), pension deficits, guarantees, and contingent liabilities can threaten solvency without appearing prominently in the Z-Score inputs.
Building a Z-Score quality screen
Conservative screen (exclude distress and most of grey zone):
- Z-Score > 2.5, or proxy: Current ratio > 2.0, Debt/Equity < 0.5, ROA > 5%, positive retained earnings
- Purpose: Produces a high-quality shortlist before applying valuation filters
Moderate screen (exclude only distress zone):
- Z-Score > 1.5, or proxy: Current ratio > 1.5, Debt/Equity < 1.0, EBIT positive
- Purpose: Wider universe that excludes obvious distress but includes financially stressed companies that may be turnarounds
Combined with value filters:
- Z-Score > 2.5 AND P/E < 18 AND EV/EBITDA < 10
- Finds: financially healthy companies at value prices — a powerful combination that avoids the "cheap for a reason" trap
Bottom line
The Altman Z-Score is a practical quantitative tool for identifying financial risk before it shows up in headlines. For stock screeners, its primary value is as a quality gate: removing distress-zone companies from value screens that would otherwise capture broken businesses masquerading as cheap stocks.
Apply Z-Score (or its proxy filters) as a first-pass quality screen, then layer valuation and growth criteria on top. The result is a candidate list where financial health is already a given, not a risk factor to investigate.