Empirical Analysis on Financial Distress Forecasting of Listed Companies in Jilin - Research based on Z-score Model

Abstract

This article discusses the early warning model of financial crisis, considering our business practice. According to financial distress prediction model of existing listed companies, it applies the Fisher discriminant method in multivariate statistical, analyzes and forecasts the financial crisis of 31 listed companies in Jilin Province, and puts forward relevant policy recommendations, which make reference to the investment decisions of investors. Index Terms - financial crisis prediction model, Z-score ratings, Fisher discriminant, financial risk 1. Summarize Z-score Model Z-score model was proposed by a well-known financial expert Edward Altman in 1968. Basic principles of Z-score model are: First, using statistical methods, analysis the company's past financial indicators statistical, select the most predictive or analytical value ratio index to reflect the Company's financial condition. Secondly, using the selected ratio indicators, design a mathematical model to maximum distinguish financial position. Finally, this model helps to assess and distinguish the company's financial condition, and put financial condition of the enterprise into two categories: bankruptcy normal and risk categories. The basic steps of establishing Z value scoring model: first, select a group financial ratios to reflect the Company's financial position, such as the liquidity ratio, return on assets, solvency indicators, etc. The second step, collect sample data of the Company, and divide the sample into two categories: one is the samples of normal financial conditions; the other is the samples of bankruptcy trends. The third step, according to the degree of influencing on the financial situation of Various ratios, select Fisher, Bayes discriminant analysis, etc, establish linear discriminant function determined by the above ratio index , determine the affect weight of each ratio, then get a Z value scoring model. The fourth step is analysis a series of Z values of selected sample, get bankruptcy threshold and the Z region, which can measure the value of the financial position. The fifth step, put the company's relevant financial data in the model can get a Z value. If the score is higher than a certain threshold or a pre-determined range, you can determine that the company's financial condition is good; if less than a values, indicate that the company has the possibility of bankruptcy. Z-score models according five financial ratios which established by Altman: 1 2 3 4 5 Z =0.012 X + 0.014 X + 0.033X + 0.006 X + 0.999 X