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Forecasting Management Of Non-Performing Assets In State-owned Commercial Banks

Posted on:2009-02-18Degree:MasterType:Thesis
Country:ChinaCandidate:X J LiFull Text:PDF
GTID:2189360272486246Subject:Technical Economics and Management
Abstract/Summary:PDF Full Text Request
During the rapid development of China's economy, commercial banks play an important role in it. But because of many factors, such as economical system, government, banks themselves and corporation etc.,a large number of bad loans has accumulated in China's financial system and credit risk has been a biggest hidden trouble among all the risks. The China's government has noticed this problem and founded four asset management corporations(AMC)to solve the occurred bad loans.Based on the analysis above, first, the paper introduces the basic conditions of non-performing assets, including the definition, the status quo, the causes and the impactes on China's economy. This was followed by the analysis of the method about forecasting the non-performing assets of China. With the results of the work of our predecessors, we do some study about the Markov model which is used to forecast the non-performing assets, and then give a prediction model which is combined with the empirical sudy. Finally, relevant preventive measures were given about the non-performing assets of state-owned commercial banks. I refer to a lot of literature information on non-performing assets of domestic and foreign banks. In the course of the study, knowledge of specific application of the Markov model is used; combine with the knowledge of economics, operations research, and other aspects.Finally, I do some empirical research and analyze the findings. The final text of the article is a summary of this paper, which contained of evaluation of the shortage and future research directions. I hope this paper can provide a new way of thinking and study for others.
Keywords/Search Tags:Non-Performing Loans of Banks, Prediction, Markov chain, Influencing Factors, Transition
PDF Full Text Request
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