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Research on the Application of Data Mining in Listed Company’s Credit Risk in China

Author: MaJia
Tutor: SuJianJun
School: Xi'an University of Science and Technology
Course: Management Science and Engineering
Keywords: Data Mining Listed companies Credit Risk Risk Measurement
CLC: F275
Type: Master's thesis
Year: 2010
Downloads: 135
Quote: 0
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Abstract


In the context of the global credit crisis continue to occur , the credit risk has become one of the main risks facing the world's financial system . The essence of the market economy is a credit economy , listed companies as an important participant of the market economy , the credit situation in particular, should be taken seriously . How to accurately measure the credit risk has also become the focus of attention of financial institutions, investors and government regulators . How to study and learn from international advanced credit risk measurement techniques , the establishment of the credit risk measurement models suitable for China's national conditions , China 's financial industry is facing an important topic . China's securities market is a huge and complex market , the establishment of a set of scientific listed company's credit risk profile assessment system , both as a regulator of the China Securities Regulatory Commission and the Stock Exchange as well as listed companies , the creditors and the majority of the investment people who have important significance. However , data mining techniques and methods continue to mature just provide a solution to the increasingly serious problem of credit risk management . The purpose of this study is that the powerful advantages of data mining technology is applied to credit risk research , data processing of the credit risk of listed companies , the method of analysis for new thinking and exploration , the use of data mining the advantage of processing data to compensate for credit risk data deficiencies. By analyzing the characteristics of credit risk data , data mining methods in the credit risk of listed companies to provide strong support . This paper analyzes the causes of the credit risk of listed companies as a research object to Mainland China 's listed companies will be special treatment (ST) as a public company into a sign of the credit crisis , selected 135 listed companies in late 2004 and late 2005 , the annual financial statements as the research sample , Spss Clementine data mining tool for the analysis and prediction of the factor analysis and logistic regression models for selected variables . The article also comprehensive utilization of the listed company's financial static data , dynamic data , combined with stock market related indicators of non-financial factors , empirical studies to measure the credit risk of listed companies in China . The empirical results show that the prediction accuracy of the model samples , the methods used in the study is valid , reasonable .

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CLC: > Economic > Economic planning and management > Enterprise economy > Corporate Financial Management
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