Empirical Study Of The Credit Risk Measurement On China's Listed Companies

With the rapid growth of credit in today's global economy, problems related to credit risk have attracted much attention. Credit risk has become one of the important risks which financial institutions have to face. How to get an accurate estimation of the credit risk plays a key role in the decision making of financial intermediaries,investors and government pay close attention to. It becomes an important task of our country's financial system to establish the credit risk models which will suitable for itself by referencing and studying the advanced credit risk measurement methods from other countries. Under this background, this paper decides to select the credit risk of China's listed companies as its research subject.This paper took an approach by combining theoretical analysis with empirical study. The main works focuses on two aspects. Firstly, analyzing KMV default model how to use to measure the credit risk of listed companies in today's China. Secondly, setting up a financial ratios system for the Logistic Regression model. Depending on this, founding the Regression model which fits to measure the credit risk of China's listed companies. The particular works as following:At the first, the paper reviewed the literatures about the credit risk measurement of other countries briefly, and introduced the research of China's scholars achieved in this field. Basing on this, the paper chose the models which are more suitable to measure the credit risk of our country's listed companies, and explaining detailedly the theories of these models. Then paper selected 84 listed companies which defaulted between the years of 2003 and 2004 as the samples, and applied KMV default model and Logistic Regression model to carry on empirical research. Results showed, KMV default model which bases on the option pricing theory could't apply directly to measure the credit risk of the listed companies in today's China, it needed further theory studying and amending. But the Logistic Regression model which depended on the corporate financial information could be used to reflect the fact of the default. Its discriminating ratio reached 90.48% for the studying samples, and also got a high discriminating ratio for the testing samples which consisted of 50 listed companies. Results also showed, the ability of solvency,management and profit were the key factors which led to the credit crisis of China's listed companies , therefore improving the level of the ability of management and profit would avoid the corporation getting into default.