BETA RISK

The probability that a false null hypothesis will be accepted by a statistical test. This is also known as a Type II error. The primary determinant of the amount of beta risk is the sample size used for the test. The larger the sample tested, the lower the beta risk becomes.

An interesting application of hypothesis testing in finance can be done using the Altman Z-score. The Z-score is a statistical model meant to predict the future bankruptcy of firms based on certain financial indicators. Statistical tests of the accuracy of the Z-Score have indicated relatively high accuracy, predicting bankruptcy within one year. These tests showed a beta risk (firms predicted to go bankrupt but did not) ranging from approximately 15 to 20%, depending on the sample being tested.

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