Fiscal Fitness of a company

An early warning system model that anticipates financial distress of supplier firms provides management of purchasing companies with a powerful tool to help identify and, it is hoped, rectify problems before they reach a crisis. Because of long-term contracts with selected and certified suppliers, large manufacturers are increasingly interested in the financial health of these suppliers in order to avoid disruption to their own production and distribution schedules.

Information that a firm is approaching distress can precipitate managerial actions to forestall problems before they occur, can invite a merger or takeover by a more solvent or better-managed enterprise, and can provide an early warning of possible future bankruptcy.  

Financial distress precedes bankruptcy. Most financial distress models actually rely on bankruptcy data, which is easier to obtain. 

Predicting the financial bankruptcy of corporations by utilising financial ratios is a subject that has been explored in different ways over last few decades and the present economic environment ensures that these models may be beneficial than ever before.

Failure prediction has become a considerable concern for stakeholders in companies.

Therefore, in order to find the most accurate model for prediction, a variety of financial ratios and failure prediction models have been applied. 

What is the Altman Z-Score

The Altman Z-score is the output of a credit-strength test that gauges a publicly traded manufacturing company's likelihood of bankruptcy. The Altman Z-score is based on five financial ratios that can calculate from data found on a company's annual report. It uses profitability, leverage, liquidity, solvency and activity to predict whether a company has high probability of being insolvent.

Finance Professor Edward Altman, developed the Altman Z-score formula in 1967, and it was published in 1968. In 2012, he released an updated version called the Altman Z-score Plus that one can use to evaluate public and private companies, manufacturing and non manufacturing companies. One can use Altman Z-score Plus to evaluate corporate credit risk.

Accuracy and effectiveness

In its initial test, the Altman Z-Score was found to be 72% accurate in predicting bankruptcy two years before the event. In a series of subsequent tests covering three periods over the next 31 years , the model was found to be approximately 80%–90% accurate in predicting bankruptcy one year before the event. (classifying the firm as bankrupt when it does not go bankrupt) of approximately 15%–20% .

From about 1985 onwards, the Z-scores gained wide acceptance by auditors, management accountants, courts, and database systems used for loan evaluation

Neither the Altman models nor other balance sheet-based models are recommended for use with financial companies. This is because of the opacity of financial companies' balance sheets and their frequent use of off-balance sheet items.

A score below 1.8 means it's likely the company is headed for bankruptcy, while companies with scores above 3 are not likely to go bankrupt. Investors can use Altman Z-scores to determine whether they should buy or sell a stock if they're concerned about the underlying company's financial strength. Investors may consider purchasing a stock if its Altman Z-Score value is closer to 3 and selling or shorting a stock if the value is closer to 1.8.

Altman Z-Scores and the Financial Crisis

In 2007, the credit ratings of specific asset-related securities had been rated higher than they should have been. The Altman Z-score indicated that the companies' risks were increasing significantly and may have been heading for bankruptcy.

Altman calculated that the median Altman Z-score of companies in 2007 was 1.81. These companies' credit ratings were equivalent to B. This indicated that 50 percent of the firms should have had lower ratings, were highly distressed and had a high probability of becoming bankrupt.

Altman's calculations led him to believe a crisis would occur and there would be a meltdown in the credit market. Altman believed the crisis would stem from corporate defaults, but the meltdown began with mortgage backed securities . However, corporations soon defaulted in 2009 at the second-highest rate in history.

BREAKING DOWN Altman Z-Score

One can calculate the Altman Z-score as follows:

Z-Score = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E

Where:

A = Working capital / Total Assets

B = Retained earnings / Total Assets

C = Earnings before interest and tax / Total Assets

D = Market value of equity / Total Liabilities

E = Net sales / Total Assets

Here are the rules for interpreting the Altman Z score.

• When Z is >= 3.0, the firm is most likely safe based on the financial data.
• When Z is 2.7 to 3.0, the company is probably safe from bankruptcy, but this is in the grey area and caution should be taken.
• When Z is 1.8 to 2.7, the company is likely to be bankrupt within 2 years.
• When Z is <= 1.8, the company is highly likely to be bankrupt.

For companies teetering on the edge of bankruptcy, it’s an easy tell.

• Overloaded debt
• Underfunded pension funds with unrealistic high returns expected
• Short term debt > long term debt
• Cash from financing > cash from operations
• and so on

A quick look at the financial statements is all that is needed to stay away from companies like this.But here’s how to use the Altman Z score to its full potential.

Break up the formula and use it as individual ratios. Lets zero in on each component. The components of the Z score isn’t rocket science.

Just simple, well thought out ratios. Let’s take a look at each of the variables and see what it can indicate in a company.

Altman A = Working Capital / Total Assets

Working Capital/Total Assets = (Current Assets – Current Liabilities)/Total Assets

This is a simple ratio to understand.

This ratio provides information about the short term financial position of the business based on the balance sheet. The more working capital there is compared to the total assets, the better the liquidity situation.

With working capital you still have to remember two points.

Point #1: Negative working capital isn’t always bad.

Companies with high inventory turnover can have negative working capital. If you take a look at Wal-Mart (WMT), it has leverage over their suppliers with favorable payment terms so their current liabilities can outweigh their current assets.

Point #2: High positive working capital isn’t always good

Just because working capital is high, it doesn’t automatically mean that it is good.It can indicate the company has too much inventory or they are not investing their excess cash.

Altman B = Retained Earnings / Total Assets

Retained earnings is the percentage of net earnings that isn’t paid out as dividends – hence the word “retained”.The company will use it to operate the business. It can be reinvested or used to pay off debt. Up to management.

But when you combine it total assets, the purpose of the ratio is now to measure how much the company relies on debt.

Makes sense.

If a company has little to no retained earnings, then it has to get money from somewhere to continue with operations. Where does that money come from? Debt or dilution.

The lower the ratio, the company is funding assets by borrowing instead of through retained earnings.

Altman C = EBIT / Total Assets

If you squint hard enough at EBIT/Total Assets, it will look familiar. It’s a variation of a common ratio that you see everywhere.

EBIT/Total Assets is a variation of ROA. Instead of net income, EBIT is used in the numerator.

ROA = Net Income/Total Assets

The definition is the same though. This ratio looks at the company’s ability to generate profits from its assets before deducting interest and taxes.

 

Altman D = Market Value of Equity / Total Liabilities

Out of the 5 components, this is the most controversial.

This ratio is supposed to show you how much of the company’s market value could decline before liabilities exceed assets.The weakness is the market value of equity, aka market cap or stock price x shares outstanding.

The problem is that if the stock price is high, then this ratio goes up.

Altman E = Net Sales / Total Assets

This ratio is just asset turnover.

I use it all the time outside of the Altman Z score as well as it is a great indicator of efficiency and business quality when comparing against previous years.

Quite simply, it is looking at the Rupee of sales generated by the company for every rupee of assets. The more money you can generate from assets, the better.

There are many reasons, both direct and indirect, that lead a company to failure. The direct reasons are under the control of the company’s directors and reflect their weaknesses and inefficiencies. However, indirect reasons are outside the control of a company’s management and they reflect the surrounding environmental conditions.

Failure is a common phenomenon that may be encountered by small and large companies in different economies, both developed and developing. Therefore, a country’s economy and society as a whole may face considerable damages and enormous costs as a result of the bankruptcy of its companies and financial organisations.

Altman Z’ score model (1983) can be considered a highly accurate and reliable model and can be utilised for predicting corporate failure.

A logit regression analysis produced a model that contained six factors:

1.    EBITDA to Sales,

2.    Current Assets to Current Liabilities,

3.    Net Fixed Assets to Total Assets,

4.    Long-Term Debt to Equity,

5.    Notes Payable to Total Assets,

6.    One-year Cash Flow Growth Rate.

The first two factors, EBITDA to Sales and Current Assets to Current Liabilities, and the last one, the annual Cash Flow Growth Rate, were negatively related to the probability that a firm would experience financial distress.

Thus, the larger these ratios, the less likely a firm would experience financial distress.

The other three factors, Net Fixed Assets to Total Assets, Long-Term Debt to Equity, and Notes Payable to Total Assets, were positively related to financial distress. For these variables, the larger the ratio, the more likely that a firm suffers from financial distress.

Source: Sec research .