What is a good financial z-score?
A score below 1.8 signals the company is likely headed for bankruptcy, while companies with scores above 3 are not likely to go bankrupt. Investors may consider purchasing a stock if its Altman Z-Score value is closer to 3 and selling, or shorting, a stock if the value is closer to 1.8.
What Is a Good Z-Score? 0 is used as the mean and indicates average Z-scores. Any positive Z-score is a good, standard score. However, a larger Z-score of around 3 shows strong financial stability and would be considered above the standard score.
A Z-score that is lower than 1.8 means that the company is in financial distress and with a high probability of going bankrupt. On the other hand, a score of 3 and above means that the company is in a safe zone and is unlikely to file for bankruptcy.
The Z-score is a metric that reveals how likely a company is going to be bankrupt or insolvent. This formula requires seven variables: Working Capital, Total Assets, Retained Earnings, Earnings Before Interest and Tax, Market Value of Equity, Total Liabilities, and Sales. The Z-score is expressed as a numerical value.
| Z-Score | Interpretation |
|---|---|
| > 2.99 | Safe Zone – Low Likelihood of Bankruptcy |
| 1.81 to 2.99 | Grey Zone – Moderate Risk of Bankruptcy |
| < 1.81 | Distress Zone – High Likelihood of Bankruptcy |
As a rule, z-scores above 2.0 (or below –2.0) are considered “unusual” values. According to the 68-95-99.7 Rule, in a normal population such scores would occur less than 5% of the time. Z-scores between -2.0 and 2.0 are considered “ordinary” values and these represent 95% of the values.
Z-scores are measured in standard deviation units.
For example, a Z-score of 1.2 shows that your observed value is 1.2 standard deviations from the mean. A Z-score of 2.5 means your observed value is 2.5 standard deviations from the mean and so on.
- 95% Two-Sided Z-Score: 1.96. One-Sided Z-Score: 1.65.
- 99% Two-Sided Z-Score: 2.58. One-Sided Z-Score: 2.33.
- 90% Two-Sided Z-Score: 1.64. One-Sided Z-Score: 1.28.
The popularity of the z-score stems from the fact that it has a clear (negative) relationship to the probability of a financial institution's insolvency, that is, the probability that the value of its assets becomes lower than the value of its debt. A higher z-score therefore implies a lower probability of insolvency.
Short Answer
A z-score equal to 2.00 will be preferred because it is a positive value, which depicts that the test score attained is 2 standard deviations greater than the mean score.
What is the best financial score?
It might be exciting to aim for 850, the highest possible FICO score, but it really comes with no additional benefits. According to credit expert John Ulzheimer, a 760 will get you the best mortgage rate and a 720 score is all you need for the best interest rate for an auto loan.
If a Z-score is equal to 0, that means that the score is equal to the mean. If the score is greater than 0 or a positive value, then that score is higher than the mean. And when a z-score results in a value less than 0 or a negative value, that means that the score is below the mean.
So, a high z-score means the data point is many standard deviations away from the mean. This could happen as a matter of course with heavy/long tailed distributions, or could signify outliers. A good first step would be good to plot a histogram or other density estimator and take a look at the distribution.
Z-SCORE BETWEEN 2.7 and 2.99 - On Alert. This zone is an area where one should exercise caution. Z-SCORE BETWEEN 1.8 and 2.7 - Good chances of the company going bankrupt within 2 years of operations from the date of financial figures given. Z-SCORE BELOW 1.80- Probability of Financial embarassment is very high.
BY doing this, we get the value as 1.6. Then we move vertically up to the z-score column. And thus, we get the value as 0.04. So, the z-score for 0.05 is 1.64.
A z-score equal to -1 represents an element, which is 1 standard deviation less than the mean; a z-score equal to -2 signifies 2 standard deviations less than the mean; etc.
If a value has a z-score equal to 0, then the value is equal to the mean. If a value has a z-score equal to -1.3, then the value is 1.3 standard deviations below the mean. If a value has a z-score equal to 2.2, then the value is 2.2 standard deviations above the mean.
If another data value displays a z score of -2, one can conclude that the data value is two standard deviations below the mean. Most values in any distribution have z scores ranging from -2 to +2. The values with z scores beyond this range are considered unusual or outliers.
For 2.5%, we have to remember that we are looking at the area beyond the Z, therefore we must subtract it from 50. 50 - 2.5= 47.5. Giving us a Z score of 1.96.
The standard score (more commonly referred to as a z-score) is a very useful statistic because it (a) allows us to calculate the probability of a score occurring within our normal distribution and (b) enables us to compare two scores that are from different normal distributions.
What is considered financially stable?
Being financially stable means you have enough money coming in to cover your expenses, as well as some extra funds to put aside for savings or potential crises. You continuously save money, you have paid your high-interest debts and you don't fret about emergencies because you're financially prepared.
If a z-score is 0, the data point is equal to the mean. For example, a z-score of +1.0 shows that the data point is one standard deviation above the mean, while a z-score of -1.0 shows the data point is one standard deviation below the mean.
It is important to note that the mean of the z scores is zero, and the standard deviation is one. z scores help to find the outliers or unusual values from any data distribution. According to the range rule of thumb, outliers or unusual values have z scores less than -2 or greater than +2.
Step 1: Compute each test score's Z-score using the mean and standard deviation for that test. Step 2: Use Z-scores to compare across data sets. Jared's Z-score of 1.48 says that his score of 92 was between 1 and 2 standard deviations above the mean.
For the majority of lending decisions most lenders use your FICO score. Calculated by the data analytics company Fair Isaac Corporation, it's based on data from credit reports about your payment history, credit mix, length of credit history and other criteria.
