The Altman Z-score is a combination of five weighted business ratios that is used to estimate the likelihood of financial distress. If the credit crunch itself wasn’t lesson enough, respected fund manager Anthony Bolton has emphasised the importance of understanding credit risk when investing in equities: “When I analysed the stocks that have lost me the most money, about two-thirds of the time it was due to weak balance sheets. You have to have your eyes open to the fact that if you are buying a company with a weak balance sheet and something changes, then that’s when you are going to be most exposed as a shareholder.”
Background to the Z-Score
The Z-Score was developed in 1968 by Edward I. Altman, an Assistant Professor of Finance at New York University, as a quantitative balance-sheet method of determining a company’s financial health. A Z-score can be calculated for all non-financial companies and the lower the score, the greater the risk of the company falling into financial distress.
The original research was based on data from publicly held manufacturers (66 firms, half of which had filed for bankruptcy). Altman calculated 22 common financial ratios for all of them and then used multiple discriminant analysis to choose a small number of those ratios that could best distinguish between a bankrupt firm and a healthy one. To test the model, Altman then calculated the Z Scores for new groups of bankrupt and nonbankrupt but sick firms (i.e. with reported deficits) in order to discover how well the Z Score model could distinguish between sick firms and the terminally ill.
The results indicated that, if the Altman Z-Score is close to or below 3, it is wise to do some serious due diligence before considering investing. The Z-score results usually have the following "Zones" of interpretation:
- Z Score above 2.99 -“Safe” Zones. The company is considered ‘Safe’ based on the financial figures only.
- 1.8 < Z < 2.99 -“Grey” Zones. There is a good chance of the company going bankrupt within the next 2 years of operations.
- Z below 1.80 -“Distress” Zones. The score indicates a high probability of distress within this time period.
The Z-score has subsequently been re-estimated based on other datasets for private manufacturing companies, as well as non-manufacturing / service companies.
Does the Altman Z-Score Work?
In its initial test, the Altman Z-Score was found to be 72% accurate in predicting bankruptcy two years prior to the event. In subsequent tests over 31 years up until 1999, the model was found to be 80-90% accurate in predicting bankruptcy one year prior to the event.
In 2009, Morgan Stanley strategy analyst, Graham Secker, used the Z-score to rank a basket of European companies. He found that the companies with weaker balance sheets underperformed the market more than two thirds of the time. Morgan Stanley also found that a company with an Altman Z-score of less than 1 tended to underperform the wider market by more than 4%.
Calculation / Definition
For public companies, the z-score is calculated as follows: 1.2*T1 + 1.4*T2 + 3.3*T3 + 0.6*T4 + 1.0*T5.
- T1 = Working Capital / Total Assets. This measures liquid assets as firm in trouble will usually experience shrinking liquidity.
- T2 = Retained Earnings / Total Assets. This indicates the cumulative profitability of the firm, as shrinking profitability is a warning sign.
- T3 = Earnings Before Interest and Taxes / Total Assets. This ratio shows how productive a company in generating earnings, relative to its size.
- T4 = Market Value of Equity / Book Value of Total Liabilities. This offers a quick test of how far the company's assets can decline before the firm becomes technically insolvent (i.e. its liabilities exceed its assets).
- T5 = Sales/ Total Assets. Asset turnover is a measure of how effectively the firm uses its assets to generate sales.
The usefulness of the original Z score measure was limited by two of the ratios.The first ratio is T4, the Market Value of Equity divided by Total Liabilities. Obviously, if a firm is not publicly traded, its equity has no market value. To deal with this, there is a revised Z score for private companies:
- Z1 = .717*T1 + .847*T2 + 3.107*T3 + .42*T4A + .998*T5 (in this case, T4 = Book Value of Equity / Total Liabilities).
The other ratio is Asset Turnover. This ratio varies significantly by industry but, because of the original sample, the Z Score expects a value that is common to manufacturing. To deal with this, there is a more general revised Z-score for non-manufacturing businesses:
- Z2 = 6.56*T1 + 3.26*T2 + 6.72*T3 + 1.05*T4A
One option is to use Standard Industrial Classification (SIC) codes to class and categorize a company as manufacturing or non-manufacturing. Companies in SIC codes 2000-3990 might be considered manufacturing companies.
NB: Both these revised measures have slightly different Zones of Interpretation.
The Altman models are generally not recommended for financial companies (hence companies in SIC Codes 6021 to 6411, 6770 to 6799 may be excluded from the universe, along with SEC codes from 8880 to 9995). This is because of the opacity of financial companies' financial statements and their frequent off-balance sheet items.
Watch Out for
The Z Score is not intended to predict when a firm will actually file for legal bankruptcy. It is instead a measure of how closely a firm resembles other firms that have filed for bankruptcy, i.e. it tries to assess the likelihood of economic bankruptcy. The model has also drawn several statistical objections over the years. The model uses unadjusted accounting data; it uses data from relatively small firms; and it uses data that is around 60 years old. Nevertheless, despite these flaws, the original Z Score model is stil the most widely used measure of corporate financial distress.
From the Source
Altman’s original paper is reasonably heavy going and you might in any case be better off reading his follow-up paper published in 2000, entitled: Predicting the Financial Distress of Companies: Revisiting the Z-Score.
There's also be a UK specific Z-score developed by Taffler.
Other Resources on Altman Z-Score
- FT article: New Study rewrites the A to Z of value investing
- Wikipedia on Altman Z-Score
- Moneyweek on Altman: How Z scores can help you beat the slump
- Europesharelab: How the Z-Score can help your investment returns