Modelling Credit Ratings
|Posted by financial-modelling.net under Finance|
Sometimes, you will need to derive interest rate assumptions from your financial model. The big agencies make their rating methodologies a secret, but there are quick and dirty approaches such as Altman's Z-Score.
At its core, a credit rating is nothing more and nothing less than a risk indicator, telling an investor how likely or unlikely an entity's bankruptcy is. The investor, be it an equity investor or a lender, will use this information to decide which return he wants to receive. While their reputation has suffered in recent years, ratings by the three major agencies Fitch, Moody's and S&P are still relied on the most. The following table shows the credit ratings for the three major rating agencies:
Option 1: Altman Z-Score
The difficulty is that the major credit agencies obviously have an interest in making their methodologies a secret. However, there has only been little effort in developing "free" credit rating algorithms. One exception is the so-called "Z-Score" by Edward Altman, originally developed in 1968.
The Z-Score is a linear combination of financial ratios, calculated as a number. Usually its result is categorised into "distress risk", "gray area" and "safe area". The original Z-Score formula is:
Z = 0.012 * T1 + 0.014 * T2 + 0.033 * T3 + 0.006 * T4 + 0.999 * T5
- T1 = Working Capital / Total Assets
- T2 = Retained Earnings / Total Assets
- T3 = EBIT / Total Assets
- T4 = Market Value of Equity / Book Value of Total Liabilities
- T5 = Sales/ Total Assets
The calculated Z then tells you about the financial standing of the company in question:
- If Z > 2.99, the company is considered "safe"
- If 1.81 < Z < 2.99, the company is considered in the "gray area"
- If Z < 1.81, the company would be in the "distress area" and is likely to be almost bankrupt
There have been variations and improvements on the Z-Score, for different industries and such, and some effort has been made to compare Z-Score results to published ratings. The Wikipedia article gives some good additional information.
Other rating methodologies
While Altman's Z Score is not the only free rating methodology, it is likely the best-documented. Developing your own rating would be a rather complex matter, but there are other good sources for inspiration. Moody's, for example, offers a very basic rating service called "RiskCalc" for which it publishes interesting documentation. For example, RiskCalc version 3.1 uses 10 financial statement ratios that differ in calculation and weighting from region to region and possibly from industry to industry: Take a look at the North American / US version and the German version. Those documents do not explain enough to ultimately "clone" the algorithm, but they give you an idea which financial ratios are important to creditors. Use them as an inspiration for the "averaging" methodology.
Option 2: Averaging
One approach that is common among professional practitioners, including the "Big 4" accounting firms, is "ratings averaging". This method requires a bigger effort than the Z-Score, but is also much more informative.
The goal here is to compare your entity's financial ratios to those of competitors that published ratings by the big rating agencies and deduct a "virtual" rating based on this comparison. This method is far from being exact, but gives you a good general idea without having to pay for a real rating:
- Decide upon financial ratios that you want to consider for your rating. It should be no less than 5, preferably 10.
- Next, find comparable companies that have public ratings for their bonds. You should find as many comparables, as possible. The criteria of choice should be industry, size, and region. Other criteria can apply, but those three are the most important.
- For those companies, you need to research the financial ratios that you decided to use in step 1. Reuters.com is a good resource for this - here with Nestlé as an example.
- Now, you need to research the ratings for those companies. Unfortunately, actually retrieving the ratings for free can be a bit bothersome. Here's where to look:
- A lot of the times you will easily find the ratings on the companies' website. Reliance Industries, Telefónica and Siemens are good examples.
- Some content on moodys.com or the other agencies' websites may be accessible for free without an account.
- Putting some time and effort into researching online, you may find free websites for your local market. For example, German speakers will find onvista.de and baadermarkets.de quite useful.