The Altman Z-Score: Is it possible to predict corporate bankruptcy using a formula?
In Brief
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.
Geek Stuff
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).
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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
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4 Comments on this Article show/hide all
Dave,
I've noticed that a number of companies seem to score low on the Altman z-score when the have negative working capital. The reason is T1 = Working Capital / Total Assets will be negative and therefore significantly reduce the z-score.
This seems to make companies that seem pretty safe to me - e.g. Cineworld (LON:CINE) as high bankruptcy risk simply because they tend to collect the money from consumers significantly before they pay suppliers and hence have negative working capital. Personally I really like businesses like this because they don't raise equity capital from me or bank debt that could be pulled to finance their working capital and I struggle to see how this massively increases their financial risk profile unless their negative WC was because they are refusing to pay suppliers on time.
Not read Altman's book so does he cover companies with negative WC. Intuitively it would seem to make more sense to use the absolute values of WC & Net Assets so:
T1 = |Working Capital| / |Total Assets|
Or am I missing something obvious here?
Cheers,
Danger
In reply to dangersimpson, post #1
Hi DM, thanks for a great comment. As I'm sure you know, negative working capital means that current liabilities exceed current assets. The reason it's used in the Altman calculation is that this fact is a strong indicator that the company could be in serious financial trouble. As you say, this is ambiguous though, as it can also be a sign of managerial or business efficiency - for example, it might be a business with low inventory and accounts receivable (which means they operate on effectively a cash basis).
Altman generally works well, in aggregate, but no statistical indicator will ever get it right 100% of the time. Financials is one known limitation and, although there is a more generic Z2 score, the original Z-Score was originally designed for "industrial companies" which typically don't have the kind of financial profile you describe. That's why we provide the popups for the Piotroski, Altman & Beneish "red flags" so users can look into specific company factors that might lead someone to draw a different conclusion.
We are not aware of any reliable adjustment factor that has been applied to weed out "good" negative working capital companies but we'll look into this further. We're also planning to implement the Distance to Default, which will be another bankruptcy risk indicator to use alongside the Altman score.
p.s. This short-selling screen is an illustration of how well it works at a portfolio level, though, notwithstanding these limitations, although its performance on the downside is eclipsed by this one.
It's also interesting to note this blog which - in discussing this very issue - argues that an alternative, fairly obvious way of screening for solvency risk is by looking for companies that show:
1. High operating risk: The top two deciles of standard deviation of EBIT or EBITDA margin over the last 5 or 10 years (pick your horizon)
2. High financial leverage: The top two deciles of financial leverage, by total debt to market equity or interest coverage. Normalized decile scores by sector.
We're actually working on an Earnings Variability indicator so we'll look at adding that too as a tracked screen to see how it compares.
p.s. We've also added a summary article on these points to the Help & FAQ section - thank for raising it:
http://help.stockopedia.co.uk/knowledgebase/articles/132951-what-are-the-known-limitations-of-the-altman-z-sco