Altman Z-Score and Distress Models

In 1968, Edward Altman of New York University combined five financial ratios into a single score that predicted corporate bankruptcy with reasonable accuracy. The Z-Score became one of the most used quantitative tools in credit analysis because it translated pages of financial data into a single number.

The intuition behind it: companies that are heading for bankruptcy typically show up in their financials well before the event, declining profitability, rising leverage, shrinking retained earnings, poor liquidity. The Z-Score captures these signals and weights them based on their historical predictive power.

While it was developed on US manufacturing data and requires calibration for Indian contexts, it remains a useful screening tool, especially for identifying companies where the score is deteriorating quickly over time, even if the absolute threshold doesn't translate directly.

Original Altman Z-Score (for public manufacturing companies):

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 (cumulative profitability / age)
• X3 = EBIT ÷ Total Assets (operating profitability)
• X4 = Market Value of Equity ÷ Book Value of Total Liabilities (market-based leverage)
• X5 = Revenue ÷ Total Assets (asset efficiency)

Interpretation (original thresholds):

• Z > 2.99: Safe zone (low distress risk)
• 1.81 < Z < 2.99: Grey zone
• Z < 1.81: Distress zone (high default risk)

Variants:

• Z'-Score: For private companies (uses book value of equity in X4 instead of market value). Thresholds: > 2.6 safe, < 1.1 distress.
• Z''-Score: For non-manufacturing / service companies (excludes X5, recalibrated coefficients). Better for Indian IT, pharma, FMCG companies.