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Study on the Revising KMV Model in Credit Risk Measurement of Chinese Listed Corporations

Author: SunJiangTao
Tutor: ZhuJinWei
School: Jiangnan University
Course: Business management
Keywords: Credit risk Credit risk measurement KMV modelDistance to default GARCH model
CLC: F276.6
Type: Master's thesis
Year: 2013
Downloads: 32
Quote: 0
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Abstract


With the deepening of financial business in China gradually, credit risk has become oneof the major financial risks and the credit risk management seemed imminent. Credit riskmeasurement as a basis for credit risk management, is the premise of science to conduct creditrisk identification. Traditional credit risk measurement methods have not already meet theneeds of scientific quantification, using sophisticated credit risk measurement technologycombined with the characteristics of China’s capital market to build up appropriate modelsand methods of credit risk measurement in China for banks and businesses, is crucial.Firstly, on the basis of credit risk measurement model theory,this paper introduced thetraditional and modern credit risk model,focused on the comparative analysis of KMV modeland other modern credit risk measure model—Credit Metrics model; Credit Risk+model;Credit Portfolio View model, Point out the applicability of KMV model in credit riskmeasurement in China. Secondly, from the two angles between banks and enterprises andenterprises of the credit risk measurement with game thoery, clarified the creditriskmeasurement’s important role in the financing process of enterprise and bank financingand between enterprises, illuminated the focus of using the KMV model to measure credit risk.Last, by pointed out the shortcomings of traditional KMVmodel and parameter correction,with70samples from2010-2012three years data, use such as ROC curve evaluation testmethod calculated the distance to default, and then constructed the KMVmodel of listingCorporations in china.The results of the study show that: the use of GARCH (1,1) model fitting stock valuevolatility, logarithmic algorithmcalculated formula of the KMVmodel’s distance to default canidentify the credit risk of China’s listing Corporation trend, distinguish between ST and nonST Company’s credit risk.but default to distance is not sensitive to default point, withdifferent default settings on the distance to default calculation does not significantly affect theresults.for samples in two groups of different operating status, revised KMV model canidentify the credit risk influencing factors’ different.ST’s distance to default is positivelyrelated with solvency, profitability, and company size, stock volatility is negatively;in nonST companies, distance to default is positively related with solvency, profitability, cash flow,and stockvolatility is negatively related.

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CLC: > Economic > Economic planning and management > Enterprise economy > A variety of enterprise and economic > Company
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