The Altman Z-Score is an analytical model that predicts the likelihood of a company bankruptcy. Altman Z-Score was released in 1968 by Edward Altman, it determines a corporate's economic health. He select 66 public manufacturing firms as data sample (50% bankrupted firms and 50% normal firms). He then analyze a few general financial ratios based on information acquired from annual financial reports. After directly connecting these ratios, he achieved an empirical equation (called the the Z-Score). This equation predicted the risk of company bankruptcy in a period of two years with a precision of 72%, and type II error at 6%. This equation was also practiced against corporate which are not in the first data sample. Altman thereafter released a remodelling called the Z1-Score, which can be practiced to private manufacturing firms, and Z2-score for non-manufacturing firms.
Financial analysis enable us to evaluate and assimilate on how the firms operate and what are the profitability of the firm. It also helps creditor, stake holder, manager,etc to make financial decision. It can significantly reduce our dependence on assumption and intuition. Not to mention that it also helps to reduce risk and uncertainty on decision making. Therefore , some techniques can be used to predict business risk or bankruptcy. The researchers use the Altman z-score analysis to analyze the likelihood of the firms bankruptcy. The main purpose of the Altman Z-score is to predict the insolvency of a firm. If the score from the Altman z-score analysis shows less than 1.81, it means that the debt of the firm has increased and the firm will face a high probability of bankruptcy.
The working capital ratio is less than one, means that there is an increase in debt of financing and current liabilities. Current liabilities increased from 3 millions to 15 millions, current ratio decreased from 72% to 33% and quick ratio decreased from 28% to 11 % within these three years. It shows that the firm has no ability to cover the maturing debts.
The firm's debt increased as a ratio of liabilities/ assets from 41.7% 56.7 % which affects its ability to obtain loans from creditors. It is necessary the firm to use its interest due to its inability to pay which the number of times interest has increased from 1.6times to 2 times. In inventory turnover, it show a decrease sign standing low assets turnover and affect the firm investment.
In the examination, Altman Z-Score gave a good indication of problems, at least one year before the company will exhibit financial problems. Success rate for prediction one year before the company failed is 66%. However, the model performed poorly when prediction time horizon increases to four years in the examination. For non-bankrupted company, Altman Z-Score model gave a good indication for companies that will not face problems even in longer span time-horizons. The result showed 78% of companies were correctly classified for the long times span which is 4 years, the percentage gradually diminished to 54% for a year time span.
Taking China as an example:
According to the official estimates, China's population has reached 1.32 billion at the end of 2007. Its economy grew by an average of 10% per year between 2000 and 2007. Due to the growth of China is getting better by an average of 10% per year; the economy of China is affected by the global crisis in year 2008 and 2009. Some companies were declared bankrupt such as shoe companies and plastic companies and caused a lot of people loss of job. Hence, China Publicly Listed Companies hope that the results may help the investors to make a good decision on their investments and improve the situation of the effect of financial crisis.
China Publicly Listed Companies compare it with other three models which are re-estimated, revised and PBT model (simple accounting based model). The results show that Altman's Z-score model has the lowest accuracy rate of 51.17% while the revised Z-score model has the highest accuracy rate of 89.79%. This is because Altman's Z-score model had classified wrongly non-delisted firms into the delisted firms with a high Type II error rate of 48.94%. Therefore, this will comprise the overall accuracy difference between Altman's Z-score model and the other three models. Furthermore, the results of all the Z-score models that investigated and the PBT model have major ability to predict firm delisting. However, Altman's Z-score model had the highest Type II error rate and performs weekly when it predicts the non-delisted firms. In accordance, revised Z-score model has the highest overall prediction accuracy of 90% in year 2010.
In conclusion, the result confirmed that the usefulness of Z-score models in predicting delisting firms. Besides, the result of those models may be affected by the immaturity and rules of China stock market. As this journal has two situations which are the companies are delisted and unprofitable for three consecutive years. Thus, PBT model will be a powerful instrument for predicting delisting firms.
Disadvantages
There are quite a lot disadvantages when it comes to Altman Z-score. Firstly, Altman Z-score analysis only focus on financial data, this certainly does not help the management department to understand the real problems in the company, as they do not know how to interpret those financial data. Secondly, the usefulness of predicting company's failure on future date and data is limited, because the value of quantitative ratios varies from time to time. Thirdly, Altman Z-score is just designed for predicting the likelihood failure of manufacturing firms. For an example, when we are applying Atman Z-score, we found out that there are many utility company that are predicted with the high bankruptcy risk, just because it is not industry specified enough. Some industry can operate with zero or negative working capital, but Altman Z-score show that the company does not score well. Another example would be a restaurant always get paid in cash and their customers normally give them net on their payables, so the inventory of the restaurant turns over very quickly. Finally, the study of Altman is during 1946, so we can't exactly portray the situation into the future situation. The models need to be adjusted, so that the ratio only can truly reflect today's financial condition.
Recommendation
Firstly, Altman Z-score might be a more useful analysis if we can use it to predict failure bankruptcy of company in a longer time zone, Altman might think to develop more effective method to formulate out a more accurate prediction formula. Further development on the Altman Z-score should be explored, Altman may think of some alternative formulas that is needed to be refined and enhance this potentially useful tool to develop a predictive tools not only for the bankruptcy, but financial distress in every kind of firms in a variety of contexts. Next way to improve Altman Z-score is using Campbell-Hilscher-Szilagy probability model which is a model to predict the aspect of future financial distress. The method they used is the simplest way to erodes the market to let firms display their high or low losses, leverage and share price. They can calcilate accurate improvement on research which had driven up the prediction of Z-score through simplest variable. Finally, I think that Altman Z-score should take more firms to study rather than only studying manufacturing industry. This is because some industries can operate with zero or negative working capital. This situation happens because their inventory is still in cash form.
Conclusion
I have learned a few things about Altman Z-score during the searching of information for this assignment. The Z-score models that have been released by Edward Altman was for the public manufacturing firms and always eliminate firms with assets less than $1 million. The return on total assets, working capital to total assets, retained earnings to total assets and the equity to debt ratio are used. All of these ratios are essential to Altman Z-score. Return on total asset measure the efficiency of operation of a company before financial and tax considerations are taken into account. Working capital to total assets measure liquidity in comparison to the size of assets. Retained earnings to total assets measure how much long-term profitability accumulates in retained earnings. Equity to debt is a formula that puts weight on a company's leverage The last ratio of sales to total assets is a measurement of efficiency of the total assets used to generate sales. I have found that it tends to be a swift peek on the likeliness of a company filing bankruptcy in working with the z-score. In my opinion,using the z-score, does not give you amazing answer. If your client is experiencing losses and has negative retained earnings, the probability that z-score will illustrate you that this company is heading towards difficulty are high.
