What is Your Company's Altman's Z Score?

What is Your Company's Altman's Z Score?

A fundamental step in determining the health of a company is the analysis of a company's historical financial statements. Historical data analysis provides a picture of the financial health of a business and a roadmap outlining the direction the business is heading. An integral part of historical analysis is the use of financial ratios. Financial ratios are analytical tools applied to financial data, which are used to identify positive and negative trends, strengths and weaknesses, investment attributes, and other trends, which measure the viability of a company's business.

Ratio analysis is typically used to measure a firm's liquidity, leverage, activity, profitability and growth. No single ratio calculation can provide a meaningful picture of a firm's financial condition. This article will focus on a model, which captures the predictive viability of a firm's financial health by using a combination of financial ratios that ultimately predicts a score, which can be used to determine the financial health of a company.

In 1968, Professor Edward Altman of the New York University School of Business developed what is known today as the "Z-Score." The Z-Score is a statistical model that incorporates the use of five different ratios, which serve to predict the health of a firm. Professor Altman believed that selecting various financial ratios and applying a certain weight to each ratio could develop a meaningful prediction model. The model was developed by sampling 66 publicly traded manufacturing companies that all had assets in excess of $1 million. Professor Altman evaluated 22 different ratios that ultimately were reduced to five balance sheet and performance ratios, which were weighted by established coefficients that account for their importance.

The following calculation is used to arrive at the total Z-Score:

Z = 1.20(X1) + 1.40 (X2) +3.30(X3) +.60(X4) + .99(X5)

X1 = Working Capital / Total Assets

X2 = Retained Earnings / Total Assets

X3 = Earnings before Interest and Taxes / Total Assets

X4 = Market Value Equity / Book Value of Total Debt

X5 = Sales / Total Assets

Z = Overall Score

The above calculation represents the overall index for a publicly traded manufacturing company. The calculation would be modified for a privately held business by implementing book value of equity because the privately held company's stock is not publicly traded. The private company Z-Score calculation would be calculated as follows:

Z = .717(X1) + .847(X2) + 3.107(X3) + .420(X4) + .998(X5)

Professor Altman further modified the formula for non-manufacturing companies by eliminating X5 (sales / total assets) due to the fact that sales / total assets can vary from industry to industry. The non-manufacturing company Z-Score would be calculated as follows:

Z = 6.56(X1) + 3.26(X2) + 6.72(X3) + 1.05(X4)

There is a different interpretation for each model. Professor Altman concluded that a Z-Score in the unhealthy category meant a company had the risk of going bankrupt, whereas a Z-Score in the healthy category represented a stable healthy company. Those companies that were in the gray area were considered misclassified.

Public Companies:
1.81 Unhealthy
1.81 - 2.99 Gray Area
2.99 Healthy

Private Companies:
1.23 Unhealthy
1.23 - 2.90 Gray Area
2.90 Healthy

Non-manufacturing Companies:
1.0 Unhealthy
 1.11 - 2.60 Gray Area ;
2.6 Healthy

The Z-Score is used by financial professionals, consultants, bankers, investors and various courts of law to measure a company's viability as an ongoing entity. Predictive models and ratio analysis are useful tools in measuring the health of a subject company. It should be noted that not every model is without shortcomings. First, ratio analysis is only as good as the underlying account data, which can be subject to manipulation. Additionally, ratio calculations can produce erroneous values when abnormal data is used.

The Z-Score is one way to provide a measure of a company's stability and its ability to function as a going concern. Many predictive models like the Z-Score provide credibility to the process. However, the Z-Score is just one method of predicting financial health and should not be the sole basis of evaluation. First hand knowledge of the operations and management are an integral part of the overall analysis necessary to come to any formal conclusions related to the final conclusion.


http://www.vercoradvisor.com/articles/CompanyScore.html

Predictions of Corporate Failure

The ability to predict corporate failure will be of interest to many stakeholders such as shareholders, lenders, suppliers, management, employee, etc. For example, banks and other lenders need to monitor loans and creditworthiness of customers, auditors need to assess the going-concern status of their clients and the companies themselves need to assess whether they are in danger of financial crisis.

Major cause of corporate failure is insolvency, which is inability to pay debts when they fall due. There are a number of reasons for a company to experience insolvency.

• One reason is overtrading which leads to shortage of working capital.
• Another is when a company invests heavily and is not able to recover its investment or earn a fair return, owing to changes in the business and economic environment and the company is not able to respond to the changes.
• Loss of major customers is also a reason, and
• Excessive amount of bad debts could lead to insolvency.

Over the last five decades considerable research has been made to determine the extent to which ratio analysis may help predict corporate failure. Often the various key ratios calculated have been done one ratio at a time. They have been grouped on some basis for inter-company comparison or comparison of performance or postion over a period fo time. It is possible to take a combination of a number of key ratios and calculate a score which is compared to a predetermined target or pass mark. When a company scores above the threshold pass mark then it is considered safe. This is referred to as multi-variate analysis or Z-score analysis. A number of models were developed to use key ratios to determine corporate failure. To date the two best-know Z-scores are Altman's Z-score and Taffler's Z-score.

How do you measure a company’s financial health?

Wednesday March 25, 2009
How do you measure a company’s financial health?
Personal Investing - By ooi Kok Hwa


Altman’s Z-Score helps investors determine the bankruptcy risk of a firm


DESPITE the recent strong stock market rally as a result of the current tough economic environment, some investors may still doubt the financial health of some listed companies.

At present, apart from some common financial ratios such as debt-to-equity and interest coverage ratios, investors are looking for a ratio that can provide an indicator on the potential bankruptcy risk for any listed companies.

In this article, we will look into a method called Altman’s Z-Score, which can help us determine the bankruptcy risk of a company.

The Altman’s Z-Score Method was developed by Dr Edward I. Altman in 1968. It is a multivariate formula to measure the financial health of a company on whether it will enter into bankruptcy in the coming two years.

This method uses five common business ratios: earnings before interest and tax (ebit)/total assets ratio; sales/total assets ratio; market value of equity/market value of total liabilities; working capital/total asset ratio and retained earnings/total assets.

The Z-Score is computed using a weighted system based on the formula below:-

Z= 3.3X1 + X2 + 0.6X3 + 1.2X4 +1.4X5

Where:

X1 = ebit/total assets

X2 = sales/total assets

X3 = market value of equity/total liabilities

X4 = working capital/total assets


X5 = retained earnings/total assets

According to Altman, if the score is 3.0 or above, bankruptcy is not likely. If the score is 1.8 or less, potential financial embarrassment is very high.

A score between 1.8 and 3.0 is the grey area where the company has a high risk of going into bankruptcy within the next two years from the date of the given financial figures.

Hence, we can conclude that we should look for companies with higher Z-Scores for investing.

We have computed Z-Scores for two listed companies, Company A and Company E. Company A is consumer-based whereas Company E is property-based. We notice that Company A has a strong Z-Score value of 5.78 versus a very low 0.62 for Company E. Based on Z-Score, Company A is very unlikely to go bankrupt (5.78>3.00) whereas the chances of Company E going into bankruptcy is very high (0.62<1.80).

The reason behind the very low Z-Score value for Company E was because it had a very low market value over its total liabilities as compared to the high market value for Company A. In fact, Company E is currently having financial difficulties and is under PN17 (Practice Notes 17).
In short, companies with higher profit margins, sales, market value, working capital and retained earnings against their total assets will command a higher Z-Score.

This method is popular in the Western countries where some accountants found it quite reliable and accurate.

In the Malaysian context, according to a user manual published by Dynaquest Sdn Bhd, they found that the cut-off at around 1.5 is a better measurement of the likelihood of bankruptcy as compared to the 1.8 stated by Altman.

It may appear that companies selling at higher market value are safer than companies with lower market value. However, sometimes we may be tempted to nibble companies with lower stock prices.

We should be aware that the current very low stock prices for certain companies may indicate to us that the coming financial results of these companies might be quite disappointing.

However, we should be aware that Z-Score does not apply to every situation. We may want to use additional financial ratio like debt-to-equity ratio to complement this method.

Ooi Kok Hwa is an investment adviser and managing partner of MRR Consulting.

http://biz.thestar.com.my/news/story.asp?file=/2009/3/25/business/3547415&sec=business