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Research on Default Probability Based on the Estimation of Bayesian Approach

Author: GuoShiMing
Tutor: WangYaJie
School: Harbin Institute of Technology
Course: Finance
Keywords: Bayesian estimation Monte Carlo simulation Rating transition matrix Credit rating process model
CLC: F832.3
Type: Master's thesis
Year: 2010
Downloads: 132
Quote: 1
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Abstract


In recent years , in the context of financial globalization , how commercial banks accurate estimates of the probability of default is an important step to improve the level of risk management . Basel II requires commercial banks to establish a rigorous statistical procedures to estimate and check the probability of default and rating transition probability . It is very difficult to establish such statistical procedures in the case of default data missing . With the deepening of China's banking industry , opening up the learning risk models used by the developed countries, the banking sector , China's banking industry to withstand a variety of international shocks has important guiding significance . This article focuses on the low default portfolio of investment-grade default probability estimation and model predictive force assessment . Potential factor model ( generalized linear mixed models ) introduced the Credit Rating Transition Model ( credit rating process model ) are discussed from a macro perspective the probability of default of the debtor by the impact of the macroeconomic situation . Fully taken into account the heterogeneity of the various credit rating of the debtor , by adding unobserved macroeconomic disturbance variables to examine the rating transfer , and using Bayesian estimation theory , in the case of rarely default data , the credit rating process model verification shows the model predictions of assessment methods . In general, the bank according to the current credit quality of each debtor , be assigned a credit rating . The credit quality of the assessment contains a number of system variables ( generated by macroeconomic disturbances ) and the debtor 's own specific variables , different companies of the same credit rating as there is often a big difference . Heterogeneity among different debtor , the typical debtor abstraction , to discuss the situation of the typical debtor's probability of default . Used two methods to test the predictive power of the model - test -sample standard deviation information (DIC) and in the case of breach of contract data missing . Finally, the transfer of credit rating , Standard \u0026 Poor's 1993-2009 datasets Asia , a comparison of the validation and generalized linear mixed models and the credit rating process model to predict the performance of the credit rating process model .

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