What is the Z score?

Definition and Examples of Z-Scores

What are Z-Scores?

A Z-score is a statistical measure that tells you how far away a data point is from the mean (or average). Z-scores can help contextualize results so that a single number makes more sense. The Altman Z-score can assist investors in determining whether a company is likely to declare bankruptcy. You may want to complement Z-score analysis with other investment research techniques before making an investment decision.

How do Z-Scores work?

Z-scores compare individual observations to the mean, and they can also help standardize information, allowing comparisons across multiple datasets. To calculate a Z-score, subtract the mean from the data point in question (data value), then divide the result by the standard deviation of the group:

Z-Score = (Observation – Mean) / Standard Deviation

Then multiply each Altman Z-score weighted component by the corresponding number. For example, X1 has a weight factor of 1.2, so it should be multiplied by 0.012. Here’s the complete calculation:

Altman Z-Score = 0.012X1 + 0.014X2 + 0.033X3 + 0.006X4 + 0.999X5

What does this mean for individual investors?

Investing in a company that declares bankruptcy can lead to significant losses. The Z-score can help determine risk, but remember it’s just one tool. Wise investors may want to dig deeper before deciding to buy or sell a stock. You might want to complement Z-score analysis with other techniques, including reviewing broader financial analysis, researching the industry and competitors, and other strategies.

Source: https://www.thebalancemoney.com/what-is-a-z-score-5197657