During the financial crisis, there were a significant number of companies in serious financial trouble. Given the number of companies going out of business and the number of investors who lost huge amounts of their savings, I thought it would be prudent to introduce a downside risk metric to evaluate investments based on their likelihood of bankruptcy.

### What Is A Z-Score?

The Z-Score is a weighted combination of 5 financial ratios used to calculate the financial strength of a company. While it is a weighted measure of several financial ratios, it basically measures liquidity and the performance of invested capital.

The knack about the Z-Score is its relative lack of any specific measurable outcomes.

### How To Read A Z-Score

The results of the Z Score test are divided into 3 general categories:

- Bankruptcy is likely – less than 1.8
- Bankruptcy is not likely – greater than 3.0
- No certain result (unsure) – between 1.8-3.0

You are probably thinking exactly what I am thinking right now… ”this doesn’t tell me anything!”

Well, we were both right and wrong.

While the Z Score doesn’t tell us much about the specific upside potential of the company, it has been accurate up to 90% in determining whether a company is likely to go bankrupt over the next year.

Therefore, using Z Score as a preliminary tool to weed out potential investments from a large group can be effective.

### How To Calculate Z-Score

Z = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E

Where:

- Z = score
- A = Working Capital/Total Assets
- B = Retained Earnings/Total Assets
- C = Earnings Before Interest & Tax/Total Assets
- D = Market Value of Equity/Total Liabilities
- E = Sales/Total Assets

It seems as though calculating the Z score for a company will provide us with a vague measuring stick that allows for the determination, with some accuracy, if a company is in dire financial trouble or not.

Generally speaking, the higher the Z score the better off financially the company is. It is my contention that, like most other indicators, it has its faults when used in isolation but can be valuable when combined with other evaluation techniques.