Z-Score is the word used in statistics to calculate the standard deviation of an observation with the mean of a data set. It helps a company determine its financial health. In particular, it is a probabilistic model for screening a company's bankruptcy risk. So what is Z-Score ? What is the formula for calculating Z-Score? Follow the article below to find out!
What is Z-Score?
Z-Score is the bankruptcy prediction coefficient. This methodology can be used to predict the likelihood that a business organization will go bankrupt within a certain period of time. Especially, mostly for about 2 years. It succeeds in predicting financial distress in every company.
[caption id="attachment_223976" align="aligncenter" width="800"]
Because bankruptcy predictors can help measure the financial health of a business organization. By using multiple balance sheet values and corporate income.
Formula to calculate Z-Score
Z-Score credit strength test. From there, it helps investors assess the bankruptcy possibility of a publicly traded manufacturing company on the market. In addition, Z-Score is based on 5 major financial ratios that can be obtained. And calculated from the company's annual financial statements.
What is the formula for calculating Z-Score?
The formula used to determine the Z-Score is as follows:
Z-Score = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E
In there:
- A = Working capital / total assets
- B = Retained earnings / total assets
- C = Earnings before interest and taxes (EBIT) / total assets
- D = Market value of equity / book value of total debt
- E = Sales / total assets
What does the Z-Score indicate?
Typically, a Z score above 2.99 indicates that a company is in a Safe Zone (based on financial metrics only). The Z-score from 1.8 to 2.99 is in the Gray Zone. This shows that there is a high risk that the company will go bankrupt within the next two years of operation. And the Z score below 1.8 is in the difficult area. This indicates a high probability of an accident during this time period.
[caption id="attachment_223980" align="aligncenter" width="640"]
The Z-Score indicates whether a data point is typical for a specified data set. Besides, Z-Score also makes it possible for analysts to apply data points from many different data sets. In order to create common values for more accurate comparison.
What is the difference between Z-Score and standard deviation?
The standard deviation of the lead indicates the degree of transformation in a given information set. To calculate the standard deviation, we first compute the difference between each information point and the mean. The standard deviation is then squared, summed, and averaged to get the variance. The standard deviation is simply the square root of the variance, reverting it back to the original unit of measure.
In contrast, the z score is the standard deviation between the given information score and the mean. To calculate the z score, simply subtract the mean for each information point and divide that result by the standard deviation.
If the Z score is negative, the information score is said to be below average. In the vast majority of large data sets, 99% of the information points have z scores between -3 and 3, indicating that they are within three standard deviations above and below the mean.
What is Altman's Z Score Plus?
Altman evolved and released altman z-score plus in 2012. This formula is applicable to both public and private valuations and can potentially be used for non-living businesses and entities. . Z-score plus is suitable for US companies and non-US companies, including businesses in hot economies, such as Vietnam as a typical example.
Limitations when using Z Score
Z-scores only have exact values and at the right time their input data is correct.
Z-score is also not very applicable to low-wage or no-money units, which would result in an extremely low z-score. Not only that, but the z-score does not contain everything about capital flows without intermediaries, but only uses the ratio of capital to net working assets. In addition, the z score changes often, but always ups and downs because it depends on the numbers from the quarterly announcement.
One key problem with the altman z-score structure is that it is not suitable for all industries. Industries that operate with a high demand for fulcrum present a greater risk of default. And industries that have to accumulate a large amount of idle cash, such as retail, will also produce companies with high risk of default.
summary
The above article introduced about what Z-Score is and related issues. Hope it will help you in assessing the business situation.