Dissertation > Excellent graduate degree dissertation topics show

Study on Credit Risk Prediction of City Commercial Banks in China

Author: XuZhu
Tutor: DongXiaoLin
School: Nanjing Agricultural College
Course: Finance
Keywords: City Commercial Banks Credit Risk Prediction PrincipleComponent Analysis Logistic Regression Model
CLC: F832.4
Type: Master's thesis
Year: 2012
Downloads: 176
Quote: 0
Read: Download Dissertation

Abstract


Since the financial crisis explosion in2008, many large commercial banks fall into financial crisis in the United States and European countries, and a large number of small and medium commercial banks have been bankrupt. Chinese banking industry is thriving; especially city commercial banks which have the largest single numbers acquire more sturdy development in this period. They not only quickly completed changing the name and the system, but also are developing toward mixing mode. However, Qilu Bank’s outbreak of serious financial fraud in January2011showed that credit risk is becoming one of the biggest risks that Chinese city commercial banks are facing, directly influencing their stability and development.According to this, this article pays attention to Logistic model’s use in Chinese city commercial banks predicting listed companies’ credit risk by using the comparing and empirical methods. The article first compares and analyzes domestic and foreign credit risk measurements and discuss various measurements’ applicability in China, then considers Logistic regression model fit to predict listed companies’ credit risk comparing with modern models such as Credit Metrics model, Credit Risk+model, Credit Portfolio View model and KMV model. That is because Logistic regression model solves nonlinear problem and has higher accuracy. After that analysis, the article chooses100listed and100non-listed companies that have complete financial data and loan in city commercial banks from2008to2010as study samples (totally600groups of data), and uses400groups of data from2008to2009as controlling groups to construct principle component Logistic regression model, which has four principle components influencing listed companies’ default probability. These four principle components are named short term debt paying ability, long term debt paying ability, income quality and operation ability, including liquidity ratio, quick ratio, speed ratio, stockholders’ equity ratio, long term assets for rate, the rate of working capital with loan, equity ratio, equity multiplier, surplus cash protection rate, inventory turnover ratio and equity turnover11key variables. Then the article uses200groups of data in2010as predicting groups to examine the principle component Logistic regression model. The average accuracy is85.57percent. The accuracy of predicting normal customers is85.71percent and the accuracy of predicting defaulting customers is85.42percent. Finally, according to the study result, this article provides same suggestions to push forward credit risk management of Chinese city commercial banks.

Related Dissertations

  1. The Brake Performance of Hydraulic Retarder and Simualtion Research on Its Application for Aircraft Arrestment,TH137.331
  2. Lifetime Prediction and Channel Wall Erosion Accelerate Test of Hall Thruster,V439.2
  3. Process Support Vector Machine and Its Application to Satellite Thermal Equilibrium Temperature Prediction,TP183
  4. Study on Quality Change and Prediction Model for Shelf-life of Chilled Pork,TS251.4
  5. Study on Quality Changes and Firmness Prediction Model of Loquat Fruit after Harvest,TS255.4
  6. A Study on the Predictive Model of Health Assessment in Li River, Guiling, Guangxi,X826
  7. Predicting Wheat Grain Yield and Quality Based on Population Indexes and Nitrogen Nutrient Status,S512.1
  8. Study on Growth Predicting Technique Based on Integration of Remotely Sensed Information and Crop Model in Rice,S511
  9. Genetic Dissection and Elite Allele Identification of Seed Traits in Soybean Cultivars Released from Huanghuai Valleys and Southern China,S565.1
  10. A Photo-Thermal Model for Predicting Growth and External Quality of Dendrobium Nobile in Greenhouse,S682.31
  11. Studies on Changes of Quality Characters and Prediction Model of Postharvest Tomato Fruit,S641.2
  12. Studies on Prediction Models for Fruit Decay and Shelf-Life of Postharvest Chinese Bayberry,S667.6
  13. Study on Growth Monitoring and Predicting Technique Based on Integration of Remote Sensed Information and Model in Wheat,S512.1
  14. Research on Key Technology of Water Prevention and Control in Kilometric Vertical Shaft Construction,TD745
  15. Study of Gray Neural Network Model of Enterprise’s Safety Devotion,X913.4
  16. Adaptive Adjustment of fire emergency plan,X928.7
  17. Zhaoguan Lower Coal Group water inrush prediction and control techniques,TD745
  18. Publishing credit Credit Risk Control Problem,G231-F
  19. Research of the Influencing Factors on Constrained Concrete Flexural Member Filled with Steel Tube,TU398.9
  20. The Market Positioning Research of China’s City Commercial Banks,F832.33
  21. Research and Application of Gas Emission Prediction Based on LS-SVM,TD712.5

CLC: > Economic > Fiscal, monetary > Finance, banking > China's financial,banking > Credit
© 2012 www.DissertationTopic.Net  Mobile