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Financial Crisis Warning Model Statistics Analysis

Author: ZhangYang
Tutor: ZhaoQingPing
School: Capital University of Economics
Course: Statistics
Keywords: Financial distress pre-waming Factor analysis method Cluster method Logit method
CLC: F832.51
Type: Master's thesis
Year: 2005
Downloads: 1565
Quote: 13
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Abstract


The stock market in our country has developed in recently years. The stock has become one of the most important investment ways. But in the whole, the revenue of listed corporations is not well. So it is urgent to build up models for financial distress pre-waming by the public financial statement of listed corporations. Based on the data acquired from listed corporations, this article analysis the financial character of difference industry first. The result revealed that the financial character between difference industries is distinct. So the pre-warning models must be built up by difference industry. By the use of factor analysis method together with the logit method, in order to make research into the financial distress pre-warning of two years. The results indicate that the models built up have satisfactory predicting accuracy. In conclusion, the article finds that the financial character between difference industries must be considerated.This research is divided into four parts:The first part introduces the theories of financial statement analysis and financial distress pre-waming and the models about financial distress pre-warning.The second part introduces the methods of financial distress pre-warning and the weakness of these methods. The article indicates the technology of statistic is important in financial distress pre-warning.The third part is empirical analysis. Include the condition of stock market、 selection of data、 analysis of financial character between difference industries and building up of models. The analysis of financial character between difference industries used the factor analysis method and cluster method. The financial distress pre-warning models used the factor analysis method and Logit method. The results indicate that the models built up have satisfactory predicting accuracy.The last part summaries the empirical result and its application, and bring up some limitation and expanding direction of this research.

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CLC: > Economic > Fiscal, monetary > Finance, banking > China's financial,banking > Financial market
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