How to use credit ratio analysis

Ratio analysis is the simplest tool for fundamental analysis. When constructing a corporate bond portfolio, it is worth starting the selection of a potential issuer with an initial selection using ratio analysis, which should then be deepened with other decision-making methods.

The most popular credit indicators can be divided into four categories:

• debt
• liquidity
• profitability
• interest coverage

All indicators are intended to answer the question of how high the risk of insolvency of a given issuer is, and the individual categories of indicators answer the questions: How much debt does the company currently have, and how easily can it settle its existing liabilities? How profitable is the business, and to what extent does servicing its debt place a burden on its operations?

The biggest challenge facing an investor in starting a ratio analysis is the appropriate selection of ratios for the analyzed industry. At the same time, remember that using ratio analysis to compare two entities with a different business profile (e.g. a furniture manufacturer to a computer game developer) will be very difficult and in some cases impossible to interpret. That is why we recommend using it to compare issuers operating in a similar business model. Ratio analysis in itself is of little use in the case of companies whose future financial results have little to do with historical data – i.e. start-ups, companies rapidly increasing the scale of their operations or computer game developers. We have also mentioned many times that investing in bonds of such ventures is much riskier than stable businesses.

In most cases, choosing the right indicator comes down to answering the question of how reliable the data used by a given indicator is, and then choosing the most reliable one. We mean here how much a given financial statement item translates into actual cash flows, and how much it results from accounting procedures. A big advantage of ratio analysis is its complete freedom – as long as we use the same indicator for the companies being compared, we can modify it at will.

Debt indicators

The most commonly used debt indicators are comparing net debt to the scale of operations – measured, for example, by the value of the balance sheet total, equity or EBITDA. Using net debt instead of gross debt has a very simple justification – cash, as the most liquid asset, can be used at any time to repay debt and it would be rather difficult to rationally justify abandoning this debt measure. As for the denominator, we have a much wider range to choose from. As we mentioned in the previous paragraph, the reliability of data plays a key role here.

The EBITDA result should not be used in the case of activities with a long period of preparation of the product for sale, i.e. housing developers. In their case, both costs and revenues are recognized only at the time of transfer of apartments to tenants, which usually takes about 2 years from the start of construction. Then, the result also recognizes the costs of land purchase, which could have been incurred many years earlier. Such high seasonality of results and comparing debt “here and now” to costs incurred in the past definitely negatively affects the reliability of such an indicator and would suggest using an indicator unrelated to the income statement. We should also abandon the EBITDA result in the case when the company has large non-cash other operating income and expenses (e.g. revaluations and creation of reserves) disturbing the clarity of the cash actually generated by the company – then we can exclude other operating income and expenses from the EBITDA result.

If we have doubts as to whether the profits of the audited company are not “paper” – that is, generated on accounting operations that do not directly translate into generated cash – we should also abandon the income statement item. In such a case, we would recommend relating the debt to the generated cash flows from operating activities.

Equity is rarely an unreliable indicator of a company’s scale, and exceptions to this rule are usually observed in individual cases, not at the level of the entire industry. The usefulness of an indicator based on equity decreases when a company has created a large profit on a difficult-to-value asset in its history – e.g. by recognizing the high value of a trademark or the value of the company’s acquired entity in intangible assets. In such a case, we would rather adjust the indicator for this specific entity by this value than abandon this measure altogether. In the case of adjustments, it is worth knowing moderation – after all, the indicator analysis is supposed to give us a general picture of the issuer’s situation, so we should limit adjustments only to those that have the greatest impact on the result.

Liquidity indicators

Liquidity ratios determine the ease with which a company can repay its liabilities within the next year. The most basic ratio, which is then adjusted to create subsequent versions of ratios, is the current liquidity ratio comparing the value of current assets to current liabilities. The ratio is adjusted by excluding from assets items that, despite being included in current assets, the company does not intend or is unable (or it is very difficult) to monetize within the next 12 months. This issue usually concerns inventories if the company capitalizes on inventories the costs of developing projects that will not be sold in the next year.

If we do not want to assess the liquidity of current assets, we can use the most restrictive of the ratios, i.e. the ratio of cash to short-term liabilities. It is worth paying attention to this ratio for informational purposes, but for the purposes of comparing several issuers it may turn out to be very unfair for a company with efficient working capital management and consciously not maintaining a high cash position. A large share of receivables overdue by more than 12 months also means that the probability of realizing all receivables within the next 12 months is doubtful – however, before we start to correct the indicator, let us ask ourselves whether the company’s business situation is safe in such a case, and only then continue the analysis.

Profitability indicators

Profitability indicators are definitely more useful in the category of comparing industries. Activities that are globally characterized by lower profitability will be more sensitive, for example, to legislative changes, which is why it is safer to invest in bonds of entities operating in industries with high rates of return and margins. The most popular among these indicators are net margin and return on equity. Of course, there is nothing to prevent us from using others in this case, if we consider such a solution appropriate.

A good measure of a company’s ability to generate cash is the use of cash flows from operating activities excluding changes in working capital. This solution has two significant advantages – it is insensitive to accounting profits and excludes maneuvers on working capital, which can perform multiple functions. For example, a company with major liquidity problems can save itself by releasing cash from inventories, which will have an impact on the future scale of operations.

Interest Coverage Ratios

The last category of indicators discussed is interest coverage indicators. Their task is to determine how problematic it is for the company to service its current debt. All indicators compare the value of funds spent on debt service to one of the company’s income items. In this case, it is worth remembering the practice of capitalizing interest on assets and using the item shown in cash flows from financial activities (which includes this capitalized interest) instead of the income statement. The most commonly used income item here is the EBITDA result, and in choosing it we should be guided by the same scheme that we explained in the previous paragraphs.

Other tools

Having such a wide range of indicators to choose from, we should not force ourselves to use all of them. If a given type of indicator is difficult to implement for the analyzed industry, we can give it up. In our opinion, for example, it is difficult to use interest coverage indicators for housing developers to be sure that the results are not distorted. Different indicators may suggest completely different results and when trying to interpret the set of issuers under consideration, a problem arises: which indicator should we take as the main point of reference.

The simplest advice in such a case is to use indicators that are most resistant to differences in accounting and non-cash one-off events. Many theorists attempt to concentrate the indicator analysis into a single and unambiguous result that answers the question about the risk of bankruptcy of a given company. Using such tools primarily allows us to compare companies from different industries, although in the case of discriminatory models one could argue with this statement.

Discriminant models

Among the tools aggregating indicator analysis, the most common are discriminant models – such as the famous Altman model. Discriminant functions define the general formula of the equation dividing a set (in this case companies) into categories (in this case, the division into safe companies and those with a high risk of bankruptcy) and are used in many fields of science. Such a function takes the form of the sum of the results of subsequent financial indicators, each of which is multiplied by a multiplier specified in advance in the model. Such a sum gives a numerical result, which is then compared with the scale prepared by the author of the model. 

For example, in the case of Altman’s model: any result below 1.81 indicates an increased risk of bankruptcy, results between 1.81 and 2.99 are ambiguous, while above 3 characterize safe companies.

x=6.56×(AssetsWorking Capital​)+3.26×(AssetsRetained Earnings​)+6.72×(AssetsOperating Profit​)+1.05×(LiabilitiesEquity​)+3.25

Using discriminative models is simpler than it seems. You just input data into an equation and compare the result to a scale. The problem with their use lies elsewhere – they are very sensitive to a highly atypical result of even one indicator (e.g. net cash instead of net debt). Such a distorted result is not always immediately noticeable, and its correction and adjustment to the given function often requires work disproportionate to the result. While discriminative models can boast significant effectiveness on a large set of companies, using them to compare 3-4 issuers may prove problematic and lead to erroneous conclusions. Moreover, such functions do not provide a clear answer to the question in which aspects the company is strong and in which it is relatively risky.

Rating models

It can be said that rating models are an improved version of discriminant models. In their case, each subsequent component is assigned to an attached scale, then a weighted average of the results is calculated using the weights provided by the model author. It is mainly such models that rating agencies use when assigning ratings to issuers. Of course, agencies significantly deepen the analysis by using many qualitative and non-numeric factors in the model, although in the most basic version you can use it yourself using the methodology that agencies often make publicly available when, for example, they switch to its improved version.

Using such a model is almost as easy as discriminant models, but the amount of information obtained from them is much greater. Such a solution is also incomparably less sensitive to atypical results of individual indicators. First of all, we receive clear information about which specific indicators indicate a good/bad situation of the company. Weights, on the other hand, unlike discriminant function multipliers, clearly show the significance of individual model components. A big advantage is also the fact that agencies prepare methodologies for various industries, and their results are easily comparable.

Summary

The main advantage of ratio analysis, in our opinion, is its great flexibility. Checking several key financial ratios can be done in a few minutes if we are under time pressure or want to make a cursory review of issuers. It can also be significantly deepened for the purposes of a reliable analysis – as we argued in this article – and obtain very detailed information on the financial situation of the issuer. 

The main disadvantage of this tool is the fact that it is based on historical data, and therefore does not always answer the question that is most troubling bondholders: whether the company will be able to repay the issued bonds. To make an investment decision, it is necessary to analyze future cash flows – e.g. the company’s investment plans and expected generated cash flows. Ratio analysis will allow us to understand how the company is currently operating and is certainly a good starting point for formulating our expectations for the future.