## The Probability of Bankruptcy

A good metric should have a low probability of rejecting a true hypothesis of bankruptcy (false positive) and a high probability of rejecting a false hypothesis of bankruptcy (false negative).

A good metric should have a low probability of rejecting a true hypothesis of bankruptcy (false positive) and a high probability of rejecting a false hypothesis of bankruptcy (false negative).

The Z-score formula for predicting bankruptcy was developed by E. Altman. The score is not intended to predict when a firm will file for bankruptcy, It is a measure of how closely a firm resembles other firms that have filed for bankruptcy.

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