Origin: Edward Altman's 1968 Study
In 1968, Edward Altman, a finance professor at New York University's Stern School of Business, published a study that would become one of the most widely used tools in credit analysis. He analyzed 66 companies — 33 that had filed for bankruptcy and 33 that had survived — and used discriminant analysis to identify which financial ratios best predicted failure.
The result was a formula that combined five ratios into a single score. In his original sample, it correctly classified 95% of the companies. Subsequent studies across different time periods and geographies have confirmed its predictive power, with accuracy rates typically between 72-90% for up to two years before a bankruptcy filing.
The Z-Score has since been cited in thousands of academic papers and is used by credit analysts, banks, auditors, and investors worldwide.
The Five Financial Ratios
Each ratio captures a different dimension of financial health. Together, they provide a comprehensive view of whether a company can meet its obligations.
X1: Working Capital / Total Assets — Measures short-term liquidity. Working capital is current assets minus current liabilities. A negative ratio means the company has more short-term obligations than short-term resources — it may struggle to pay its bills.
X2: Retained Earnings / Total Assets — Measures cumulative profitability over the company's life. A low ratio means the company has either been unprofitable historically or has been distributing most of its earnings. Young companies naturally score lower here.
X3: EBIT / Total Assets — Measures current operating efficiency. Earnings Before Interest and Taxes relative to total assets shows how productive the company's assets are. This is the most powerful predictor of the five — a company that can't generate operating income from its assets is in trouble.
X4: Market Value of Equity / Total Liabilities — Measures the market's assessment relative to obligations. This is the only market-based ratio in the model. When the market cap drops below total liabilities, it signals the market believes the company may not be able to cover its debts.
X5: Revenue / Total Assets — Measures asset utilization. How efficiently does the company use its assets to generate revenue? A declining ratio can indicate excess capacity or asset impairment.
The Formula and Weights
The Z-Score formula for public manufacturing companies:
Z = 1.2(X1) + 1.4(X2) + 3.3(X3) + 0.6(X4) + 1.0(X5)
The weights reflect each ratio's predictive power. X3 (EBIT/Total Assets) carries the highest weight at 3.3, confirming that operating profitability is the strongest predictor of survival. X2 (Retained Earnings/Total Assets) at 1.4 reflects the importance of cumulative profitability.
All five inputs come from the company's financial statements (10-K filing) except X4's market value, which uses the current stock price times shares outstanding.
Three Zones: Distress, Gray, Safe
Altman's original cutoff points, which have been validated across decades of data:
Distress Zone (Z < 1.8) — High probability of bankruptcy within two years. The balance sheet is under significant stress. Companies here typically have negative working capital, low or negative retained earnings, and operating losses.
Gray Zone (1.8 ≤ Z ≤ 3.0) — Elevated uncertainty. The company isn't in immediate danger, but the financial position has vulnerabilities. Many companies in this zone are cyclical businesses in a downturn or companies with high leverage that's still serviceable.
Safe Zone (Z > 3.0) — Financially healthy. The company has a strong balance sheet with adequate liquidity, profitable operations, and manageable debt levels. Bankruptcy within two years is very unlikely.
The trend matters as much as the absolute number. A Z-Score of 2.5 that has been declining for three years is more concerning than a Z-Score of 1.9 that has been improving.
How Accurate Is It?
Altman's original 1968 study: 95% accuracy in the sample (but this was in-sample, so overfitting is expected).
Subsequent out-of-sample studies:
- 72% accuracy one year before bankruptcy (Altman, 2000 review)
- 80-90% accuracy for manufacturing firms within two years
- Lower accuracy for service and financial companies
- Accuracy improves when combined with trend analysis
The Z-Score is best used as a screening tool — a first filter to identify companies that need deeper investigation, not a definitive bankruptcy prediction.
Limitations and Variants
Financial companies: Banks, insurance companies, and REITs have fundamentally different balance sheet structures. The Z-Score was not designed for them and produces unreliable results.
Young companies: The retained earnings ratio (X2) penalizes young companies that haven't had time to accumulate earnings, even if they're growing rapidly and well-funded.
Accounting differences: International accounting standards (IFRS vs. GAAP) can affect the ratios. Companies using different depreciation methods or revenue recognition policies may produce different Z-Scores from comparable businesses.
Variants: Altman developed the Z'-Score for private companies (replacing market cap with book value of equity in X4) and the Z''-Score for non-manufacturing and emerging market companies (removing X5 entirely). Both use different weights and cutoff points.
How FairValueLabs Uses the Z-Score
We calculate the Altman Z-Score for every stock in our coverage using data pulled directly from SEC EDGAR 10-K filings. Our pipeline:
- Extracts the five required financial data points from the latest filing
- Calculates each ratio and the weighted Z-Score
- Classifies the company into distress, gray, or safe zone
- Calculates the Z-Score for each of the past 10 years to show the trend
- Flags companies where the Z-Score is declining toward the distress zone
The Z-Score is one of four metrics on every ticker analysis page, alongside DCF fair value, moat rating, and dividend safety. Visit the Risk Audit section to explore companies by risk level.