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Altman Z-Score: Financial Distress Formula and Limits

For educational purposes only; not investment advice.

Direct answer

Section titled “Direct answer”

The Altman Z-Score is a financial-distress screening model that combines five accounting and market ratios into one score. The classic public manufacturing-company version is:

Z = 1.2X₁ + 1.4X₂ + 3.3X₃ + 0.6X₄ + 1.0X₅

where X₁ is working capital divided by total assets, X₂ is retained earnings divided by total assets, X₃ is EBIT divided by total assets, X₄ is market value of equity divided by book value of total liabilities, and X₅ is sales divided by total assets.

The score is useful for risk screening, not for certainty. A low score does not prove bankruptcy, and a high score does not eliminate refinancing, liquidity, fraud, industry, or market risk.

What the five variables measure

Section titled “What the five variables measure”

X₁ = working capital / total assets measures short-term liquidity. Working capital is current assets minus current liabilities. A negative value can point to funding pressure, although some retailers and subscription businesses can operate with structurally low working capital.

X₂ = retained earnings / total assets measures accumulated profitability and age. A mature company with years of retained profit usually scores better than a young company that has not yet built retained earnings.

X₃ = EBIT / total assets measures operating earning power before interest and taxes. It receives a large weight because deteriorating operating returns often appear before formal distress.

X₄ = market value of equity / book value of total liabilities measures the market cushion protecting creditors. It can move quickly because the equity value changes with the stock price.

X₅ = sales / total assets measures asset turnover. It is industry-sensitive: a software company, manufacturer, utility, and retailer can have very different normal turnover.

Classic discussions often use zones such as distress, gray, and safer areas. Those cutoffs came from particular samples and periods. Apply them cautiously, especially outside public manufacturing companies.

Worked example

Section titled “Worked example”

Assume a manufacturing company reports:

  • current assets: $600 million
  • current liabilities: $400 million
  • retained earnings: $300 million
  • EBIT: $120 million
  • total assets: $1.0 billion
  • market value of equity: $800 million
  • total liabilities: $500 million
  • annual sales: $1.5 billion

The variables are:

X₁ = ($600m - $400m) / $1,000m = 0.20

X₂ = $300m / $1,000m = 0.30

X₃ = $120m / $1,000m = 0.12

X₄ = $800m / $500m = 1.60

X₅ = $1,500m / $1,000m = 1.50

The score is:

Z = 1.2×0.20 + 1.4×0.30 + 3.3×0.12 + 0.6×1.60 + 1.0×1.50

Z = 0.24 + 0.42 + 0.396 + 0.96 + 1.50 = 3.516

Now suppose the stock price falls so the equity market value drops to $300 million and EBIT falls to $40 million. Then X₄ = 0.60 and X₃ = 0.04. Holding other inputs constant:

Z = 0.24 + 0.42 + 0.132 + 0.36 + 1.50 = 2.652

The score worsens because operating profit and market cushion declined. It still requires context: debt maturity, cash access, covenants, industry conditions, and management actions can change the outcome.

Limits and practical checks

Section titled “Limits and practical checks”
  • Use the correct model version. The classic formula was built for public manufacturing companies; private firms, financial firms, utilities, and service businesses may need different treatment.
  • Check accounting quality. One-time gains, leases, revenue recognition, inventory write-downs, and pension assumptions can affect inputs.
  • Do not ignore timing. Balance-sheet values are point-in-time, while sales and EBIT cover a period.
  • Market value can be circular. A falling stock price reduces X₄, making the score worse during market stress.
  • Compare with liquidity evidence: cash, revolver access, debt maturities, covenants, free cash flow, and credit ratings.
  • Track the trend, not only one number. A score falling over several periods can be more informative than one isolated reading.
  • Combine the score with 10-K risk factors, MD&A, footnotes, and cash-flow analysis.

Common misconceptions

Section titled “Common misconceptions”

“The Z-Score predicts bankruptcy exactly.” It is a statistical screening model, not a legal or time-specific bankruptcy forecast.

“Higher is always better across every industry.” Asset turnover and working-capital norms vary widely by industry.

“A company with a low score is uninvestable.” Low scores flag distress risk. Securities can still have value, but the required return, downside risk, and capital-structure position become central.

“The formula replaces reading filings.” The variables come from filings and market data; they do not replace understanding the business, debt terms, or cash-flow path.

Section titled “Related topics”

Authoritative sources

Section titled “Authoritative sources”