Ohlson's O-Score

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Definition

Created by James Ohlson in the 1980s, the Ohlson Score uses items from the financial statement to predict the likelihood of a firm's bankruptcy. The O-Score breaks it down into nine different approximate measures of a firm's default risk, two of the nine being dummy variables: these nine are used to determine firm size, leverage, working capital, liquidity, profitability, change in net income, and debt financing. Together, these nine variables build an O-Score where the probability of failure is EXP(O-Score) divided by 1+EXP(O-score). Results greater than >.5 indicate a firm with a high chance of default.

It has been argued that the Ohlson Score is a better predictor of bankruptcy than other similar accounting models such as the Altman Z-Score, however, investors may find merits in using both Altman and Ohlson in helping to predict a firm's bankruptcy.

Because both Ohlson and Altman use an accounting-based model to help predict bankruptcy, its strength is its relatively simplicity. However, there are other bankruptcy models such as Merton's Distance to Default and CHS are other bankruptcy models that are used by academics and argued to be more effective in predicting bankruptcy risk.

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