The Altman Z-score is a measure developed by Edward Altman, who was a finance professor at New York University. It helps predict the likelihood of a company facing financial distress to default within the next two years. It does this by analysing the company's current financial data.
The Z-score formula for the manufacturing companies is:
Z = 1.2T1 + 1.4T2 + 3.3T3 + 0.6T4 + 1T5
T1 = Working capital / Total assets (Measures liquid assets in relation to the size of the company).
T2 = Retained earnings / Total assets (Measures profitability that reflects the company's age and earning power).
T3 = Earnings before Interest and Taxes / Total assets (Measures operating efficiency apart from tax and leveraging factors. It recognises operating earnings as being important to long-term viability).
T4 = Market value of Equity / Book value of total liabilities (Adds market dimension that can show up security price fluctuation as a possible red flag).
T5 = Sales/ Total assets (Standard measure for total asset turnover).
Z > 2.99 are considered in 'Safe' zones
1.81 < Z < 2.99 are considered in 'Grey' zones
Z < 1.81 are considered in the 'Distress' zones
Z-score estimated for non-manufacturers companies is:
Z = 6.56T1 + 3.26T2 + 6.72T3 + 1.05T4
T1 = Working capital / Total assets
T2 = Retained earnings / Total assets
T3 = Earnings before Interest and Taxes / Total assets
T4 = Market value of Equity / Total liabilities
Z > 2.6 are considered in 'Safe' zone
1.1 < Z < 2.6 are considered in 'Grey' zone
Z < 1.1 are considered in the 'Distress' zone
The Piotroski F-score was developed by Joseph Piotroski, an accounting professor at the University of Chicago. It assesses the overall financial strength of a company.
The score ranges from 0 to 9, with 9 being the best. The score is determined based on nine different criteria. If a criterion is met, the company earns one point, and if it is not met, no points are awarded.
The first four criteria of the Piotroski score focus on measuring profitability:
- Positive net income compared to the previous year.
- Positive operating cash flow in the current year.
- Higher return on assets (ROA) in the current period compared to the previous year.
- Cash flow from operations greater than net income.
The next three criteria assess the health of the balance sheet by looking at debt and the number of shares outstanding:
- A lower ratio of long-term debt in the current period compared to the previous year.
- A higher current ratio this year compared to the previous year.
- No new shares were issued in the last year.
The last two criteria of the Piotroski score examine operating efficiency:
- A higher gross margin compared to the previous year.
- A higher asset turnover ratio compared to the previous year.
A score of 8 or 9 is considered strong, while a score between 0 and 2 indicates a weak stock.
We have developed a Modified C-score that uses a quantitative method to assess the likelihood of financial manipulations. It is based on James Montier's C-score, which consists of six checks to detect red flags for earnings manipulation. We have added three additional points to further improve the score's accuracy.
Each company is assigned a value of zero or one based on qualification, and the higher the C-score, the higher the probability of financial manipulation.
James Montier's C-Score
Montier's C-score consists of six red flags that indicate possible earnings manipulation. The scoring is simple, with a value of 1 for yes and 0 for no. The total score ranges from 0 (no evidence of earnings manipulation) to 6.
The individual tests are:
- Is there a growing gap between net income and operating cash flow?
- Are Days Sales Outstanding (DSO) increasing?
- Are Sales of Inventory (DSI) increasing?
- Are other current assets increasing compared to revenues?
- Are there declines in depreciation relative to gross property, plant and equipment?
- Is total asset growth high?
Our additional checks:
- Are debtors as a percentage of revenue increasing?
- Is asset quality improving or declining?
- Is the accrual ratio high or low?
These checks help identify potential financial manipulations based on factors like cash realisation, asset quality, and the difference between accrual accounting and actual cash earnings.