论文信息 - Generalized Autoregressive Conditional Heteroskedasticity in Credit Risk Measurement

Generalized Autoregressive Conditional Heteroskedasticity in Credit Risk Measurement

This paper presents a modified model for Chinese credit risk management. The model is based on KMV model with consideration of Generalized Autoregressive Conditional Heteroskedasticit (GARCH). Data used in this research are from the balance sheet and the Chinese stock market. T-tests and ROC curves are employed to analyze the data, examining the model. It is shown that the model can be applied to identification and measurement of the credit risk of companies and hence offers an efficient way to banks in risk management.

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