## 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.

Historic growth is usually a risky estimate for future growth. To be able to forecast a company’s future performance you have to make assumptions on the future most likely values ….

Audits done shows that nearly 90% of the spreadsheets contained serious errors. Code inspection experiments also shows that even experienced users have a hard time finding errors succeeding in only finding 54% on average.

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