# Risk prediction based on financial statements

I have a profit loss statement and balance sheet with the following fields: Example

P&L
Turnover420,363 -
Cost of sales             £118,730    £140,169    -
Gross Profit                £178,862    £280,194    -
Operating Costs           £154,889    £255,123    -
Interest paid (received)  £3,007  £4  -
Tax paid  -               £4,838  -
Profit After Tax (Loss)     £20,966 £20,229 -

Balance Sheet
Total assets                £68,090 £47,032
Current assets            £62,975 £43,847
Fixed assets              £5,115  £3,185
Total liabilities           £56,560 £55,731
Current liabilities       £56,560 £55,731
Long-term liabilities     -   -
Shareholder Funds / Net Assets £11,530  £(8,699)


I'd be interested in what models exist to predict credit risk or bankruptcy likelihood based on this information. (I have other meta data available as well, such as industry and location, but I ignore that for the moment)

After researching for a while I found this paper by Altman http://onlinelibrary.wiley.com/doi/10.1111/j.1540-6261.1968.tb00843.x/full He uses a method called Z-score that is the linear combination of five financial ratios. wikipedia Is this still widely used today? If not what are the alternatives?

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I do not see how this relates to quantitative finance, given financial statement analysis is pretty much the antidote to financial mathematics. With all the accounting gimmicks (some corporations hold more off-balance sheet assets and liabilities than on-balance) its a moot point to derive meaningful conclusions regarding risk and expected return by looking at financial statements only. Sadly, in today's time the CFO's most valued skill set is in making accountants sign off on massaged balance sheets and income statements. What more to say? – Matt Wolf Jun 4 '13 at 2:56

If you don’t have any market quotes, one possible way to assess the credit risk of a company is to use its financial statement information in order to infer the corporate rating that credit agencies might have assigned to such company.

For instance, in this paper you can find the general criteria that S&P use to derive the credit rating of a company based on its financial information.

In particular, indicative ratings might be calculated using three financial ratios: FFO/Debt, Debt/EBITDA and Debt/Capital. In addition, you would also need to estimate the company business risk profile (country & industry risk, competitive position, etc.)

Once you have the financial and business risk profile, a theoretical rating for the company might be obtained using the risk matrix provided by S&P.

Finally, once you have the credit rating, two possible ways to infer the company credit risk will be:

1. Search for bond indexes or bonds issued by companies with the same credit rating and derive their credit spread (if possible using companies of the same sector and bonds issued in the same currency)

2. Look at the default rates that have been observed in the past for companies of similar rating (also provided by S&P)

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RMS-Z cmbi.kun.nl/mcsis/richardn/RMS-Z.html and A NOTE ON STANDARD DEVIATION AND RMS user.gs.rmit.edu.au/rod/files/publications/St_dev.pdf – montyhall Jul 6 '13 at 10:40

You maybe want to have a look at this paper

Are Ratings the Worst Form of Credit Assessment Apart from All the Others?

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Can you provide a summary of this paper? – chrisaycock Jun 5 '13 at 11:14

You can start exploring the subject by having a look at Credit risk measurement: Developments over the last 20 years if only for the reference list. As a more modern approach an "upgraded" version of the original Z-score method was recently proposed by Altman: Z-Metrics™ Methodology For Estimating Company Credit.

Though be aware that despite numerous alternative methods being available (just search for discriminant analysis), most of the time you could describe the process as fitting a simple model to the available training/test data set. So the question you have to answer before all is about the appropriateness of the assumptions to your situation (analyzed universe, regime changes etc.). Quality of data is also an issue as already mentioned by @MattWolf.

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Z-metric might be what I'm looking for because my data concerns small private companies that are not listed on the stock market. – siamii Jun 5 '13 at 14:15