What bankruptcy prediction model uses nine financial ratios to compute an O-score?

The bankruptcy prediction model that computes an O-score from nine weighted financial factors is the Ohlson O-score. James Ohlson proposed it in 1980 as an alternative to the better-known Altman Z-score.

The model combines information from standard financial statements, including total assets, total liabilities, working capital, current liabilities, current assets, net income and funds from operations. It also includes indicator variables for insolvency and recent losses, plus a size adjustment based on the gross national product price index.

The O-score is a logit-style distress measure: applying the logistic transformation to the score produces an estimated probability of failure. In the original formulation, the model was developed from a sample of more than 2,000 companies, substantially larger than the 66-company sample used for Altman’s original Z-score.

The nine-factor structure does not make the model infallible. Accounting choices, economic conditions and industry differences affect its usefulness, and later research has produced other distress models. The Ohlson model is also distinct from the Zmijewski and Springate models, which use different variables and formulas.