The Empirical Research Of Listed Companies’ Credit Risk Measurement

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. The lack of suitable credit risk measurement model stomonitor Chinese listed companies and their transactions’associated is a big problem to the credit risk management. Through reference and learning international advanced credit risk management techniques and methods to establish suitable the credit risk measurement of models and methods is an important topic to the credit risk management. This article to carry out relevant research measure on the credit risk of listed companies in China. 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 work focuses on 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 selected88listed companies which defaulted between the years of2008and2010as 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 in formation could be used to reflect the fact of the default. Its discriminating ratio reached88.43%for the studying samples. Results also showed, the ability of solvency, operation, development 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.