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Financial Distress of Listed Companies

Author: ZhaoGuoZhong From: www.yourpaper.net Posted: 2009-04-02 18:16:21 Read:
Abstract select special treatment due to abnormal financial position of listed companies in 2004-2006 (referred to as ST Company), and select the same industry and similar size normal Inc. (nst) as paired samples. The comparison between the company's financial indicators mean, as well as analysis of the value of t, summed up the characteristics of the company's financial crisis indicators. Trying to explore various financial indicators of financial distress of listed companies on the basis of the analysis of the causes of listed companies' financial crisis early warning role.
Keywords Financial crisis; listed companies; financial indicators

Introduction

With the continuous development and improvement of the capital market, listed companies' financial crisis early warning has been one of the hot issues of the academic circles at home and abroad. Enterprises, corporate investors, creditors, employees within the company and other relevant stakeholders have different levels of financial distress Therefore, it is possible to use the financial information to accurately predict the financial crisis, have important implications for businesses and all aspects of society.
Financial crisis the (Financial c risis), also known as financial distress (FlnanciaIdjstress), foreign scholars generally bankruptcy as a standard to expand the research. 's Insolvency mechanism is not perfect. At present, the vast majority of the scholars listed companies to special treatment as the research object (Suggestions of How to Construct the Modes, Chen Zhibin 2007).

Second, the literature review and research methods

(A) foreign literature review and research methods
Fitzpatrick (1932) carried out univariate bankruptcy prediction. Him as a sample of 19 companies. The use of a single financial ratio divides the sample into bankruptcy and non-bankruptcy two groups, he found that the ability to judge the highest net profit / shareholders 'equity and shareholders' equity / liabilities two ratios. Beaver (1966) univariate decision model. He uses cash flow / liabilities, current assets / current liabilities, net income / assets, asset-liability ratio, working capital / assets of five financial ratios as variables, the use of empirical analyzes cash flow to total liabilities ratio are better able to determine the company's financial position. Followed by the asset-liability ratio. AItman (1968) proposed that multiple Z-value model. Certain variables are combined into a functional equation. Z value is determined, the results show that. In the bankruptcy of the previous year's predictive accuracy is greatly improved compared to the Beaver. AItman, Haldeman and Narayanan in 1977 proposed a more accurate prediction of the new model of corporate financial failure - ZETA model. BIum (974) to assess the possibility of an enterprise financial crisis in cash flow point of view. Multiple discriminant analysis research methods to construct a financial crisis prediction model, including liquidity, profitability and variability of 12 financial ratios with six variability index ". The results show that the model correctly predicted a higher rate for the five years before the financial crisis in the enterprise. 1977 Marttin the first time in the financial crisis early warning studies using multivariate logit regression method to obtain a good prediction. OhIson (1980) 9 Financial Ratios construct three logit model, empirical results show that four financial information to assess the probability of bankruptcy is statistically significant. Odom and Sharda (1 990), the first successful use of artificial neural network (ANN) to predict the financial crisis. Coats and Fant (1991) 47 financial crisis and 47 normal use of neural network model to discriminate when. Financial crisis prediction accuracy rate was significantly higher than that the multiple discriminant accuracy of the law.

(B) the domestic literature review and research methods
The Chinese scholars Chen Jing (1999) Beaver and Altman model. Selected 1995-1997 27 crisis, and 27 in the same industry, the empirical research with the scale of the company's financial data. Obtained prediction model valid conclusions on the Chinese market. Chen Xiao, Chen Zhihong (2000), the multiple logistic regression model into the listed company's financial crisis forecasts. Zhang Ling (2000) 120 listed companies as the objects, the use of 60 of the company's financial data to estimate the second-class linear discriminant model and 60 model checking. Found that the model has four years ahead of forecast results. The Wu Shinong, Luxian Yi (2001) univariate judgment, multivariate linear discriminant and multiple logistic regression method. Were established distress prediction model. The results prove that. These models are the higher accuracy of the determination, less than 28% false positive rate in the four years before the financial crisis. Zhang Aimin, I wish Spring Hill (2001), principal component analysis combined with the Z-score model establishment of early warning models. The empirical tests show that this method deal with the study variables the model has good predictive ability. Yang Pao (2001), Xue Feng (2002) to explore the neural network BP algorithm and LM algorithm based on the forecast of the enterprise financial crisis. Hepei Li, Zhang early Li (2002) established discriminant model timing three-dimensional data space based on the financial crisis, before they Logit regression analysis using the global principal component analysis, thereby enhancing the validity of the model. Model accuracy rate of 71.3%. The LV Changjiang, China (2005) Manufacturing Listed Companies 1999-2002 data, respectively, using multiple discriminant analysis, comparative analysis the logical linear regression model and artificial neural network model is in crisis on the financial position of the company to predict. The results showed that: Despite the use of the model has its specific prerequisite three mainstream models could be one year before the crisis in the company and the first 2-3 years of better forecast. Therein. Multiple discriminant analysis to be inferior to the logic model, the highest of the prediction accuracy of the neural network model. Xiao Yan (2004) the traditional financial indicators and cash flow indicators, use the the Logit method to build a listing of the company's financial crisis early warning model, the modeling sample prediction accuracy rate of 98.1%, the samples tested in the prediction accuracy rate of 91.1%. Zhang Ming (2004) that the audit opinion to a certain extent, reveal the business potential risks. The information content of the financial crisis early warning. CHEN Liang-Hua (2005) Logit regression on the Shanghai Stock Exchange study found that the proportion of independent directors, the proportion of the largest shareholder, cash flow rights and voting rights deviate from the governance structure variables do with the financial crisis there is a correlation, the introduction of these indicators The model can achieve high prediction accuracy. LI Bing-cheng (2005) induction summarizes the causes of the listed companies' financial crisis. Management scorecard (A scoring method). Quantify the qualitative factors, listed companies' financial crisis "A scorecard analysis model. Lu Jun (2006) argues that non-financial indicators build financial crisis prediction precision of the model does not decrease with time goes forward non-financial indicators can reflect the characteristics of the crisis, but more fundamentally. And to some extent explain the reasons for the financial crisis.
From the literature review, the company on the financial crisis at home and abroad using the financial indicators and non-financial indicators, this paper also used financial indicators of financial crisis early warning research.

Third, the study sample and study variables

Selected 131 listed companies in 2004-2006 due to abnormal financial status and special treatment for the sample, while using paired sample design method to select the same industry (SFC industry code classification) of similar size (total assets) 131 normal home as a paired samples. Since the crisis after the announcement of the Annual Report, abnormal financial position, result in ST, select the observation period. Let ST 1 year ago t, 2,3,4 years ago, respectively, t-1, t-2 and t-3. Take t-3 to t-financial indicators as variables. Paired samples taken the same period corresponding financial indicators.
The data from CSMAR the listed companies' financial indicators database (2006). The first sample Firms in the top 14 for the vast majority of financial indicators data from the listed in the CSMAR database. Paired samples and then extracted four years of financial data. Financial indicators listed sample data. By the the annual installments crisis normal are classified, respectively, each of the financial indicators of the two sets of data. Use SPSSl 4.0 for data processing.
In this paper, the financial indicators as variable. The main features of China's listed companies in financial crisis companies can not repay maturing debt, the working poor, poor profitability, insufficient cash flow and limited capacity. This paper from the selected 19 key financial indicators reflect corporate solvency, profitability, operational capacity, capacity development and cash flow. Build pre-selected indicators of the financial crisis, by calculating the mean of the financial indicators and to measure the degree of difference in mean values ??of t. Research distress.

, Statistical Research

(A) the solvency indicators of
Corporate solvency indicators include two types of short-term solvency indicators and long-term solvency indicators.
1 short-term solvency indicators
Select the current ratio, quick ratio, and working capital to total assets ratio three indicators to analyze the characteristics of the financial crisis, the the three indicators mean and measure the degree of difference between the t values ??are shown in Table 1.
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