Research On Credit Risk Measuremen Model Based On KMV Optimization

In our country, the major risks to the financial industry is from the credit risk, thedevelopment level and extent of the financial sector stabilization determines thestability of our economy, the credit risk must get sufficient attention as an importantcontent of the financial sector so that the financial sector to be able to betterdevelopment and the national economy can seek progress.so the measurement andmanagement system of the credit risk is particularly important，By throughing theforeign advanced measuring technology and correlation analysis of the credit risk intoour country, to measurement and research on Chinese credit risk, what is theresponsibility and important issue to the relevant academic urgent.The measurement of credit risk and the related use of the model in our countryrelatively late, so China needs to learn from foreign advanced technology,meanwhile, we need to seriously consider China’s actual situation, to amend therelevant measurement techniques optimized in order that it can effectively meet ouractual situation, to measure credit risk situation the most effective in the greatestextent. Therefore the thesis mainly by KMV model for the study proposed aoptimization methods and measures for KMV model. Through empiricalanalysis,validation and summarizes the optimized KMV model for credit riskmeasurement results.The thesis first introduces the management practices and processes about creditrisk, as well as related content KMV model relevant indicators of credit riskmeasurement models, etc. Description of the important role of credit riskmeasurement and management in our risk management system and economic activity,and thus proposed a target rate of return on net assets at the core of KMV credit riskmeasurement model，to analyze sources of ROE data indicating, the advantages of themeasurement process, and the relevant measurement equation and measurementmethods.Then, the thesis as ROE indicators to the core of the model to be validated bythe factoring bank listed companies in our former Sea region, as the example,analyzes differences using optimization measuring in KMV model of different enterprises about ST and non-ST companies. The thesis data selected ROE with dataDecember31,2012ending, validated optimization of the KMV model. The empiricalresults show that the optimized KMV model can effectively distinguish companiesbusiness with ST and non-ST, while the optimizing KMV risk measurement model ismore timely, sensitive and accurate, KMV model greatly expands the scope of use ofrisk KMV model，improves the predictive power of a good market for China’seconomic development has laid a stable foundation.