Bankruptcy prediction models use historic corporate accounting and market data to mathematically evaluate a firm’s probability of entering formal liquidation.

Core Frameworks

• Multivariate Discriminant Models: Statistical approaches (like the Altman Z-Score) that weigh and combine multiple ratios to maximize predictive accuracy.

• Logit Probability Models: Non-linear statistical methods (e.g., Ohlson’s O-Score) that output a definitive, direct probability percentage of structural default risk.

• Market-Based Structural Models: Models (such as the Merton Distance-to-Default framework) that use equity option prices and market volatility to estimate default likelihood.