Research On Information Effectiveness Of Credit Risk In Stock And Corporate Bond Price

With the development of global credit economy, the credit risk gradually becomes an important risk which can trigger the financial crisis. In risk monitoring, however, what financial institutions have done were unsatisfactory. Because the current mainstream methods of credit risk measurement are mostly financial analysis that is based on backward-looking historical data, leading to the fact that this kind of method can’t identify credit risks timely. From the end of last century, scholars began to explore news methods, and the representative models are based on the financial market prices, such as KMV model and credit spreads model(CS model). These two models are based on market price information to monitor credit risk, which determines they only apply to the efficient market. So, before applying these two models, it is necessary to study the information effectiveness of credit risk in stock and corporate bond price.With the increasing of China’s credit economy, it is very important for economic stability to establish a real-time monitoring system of credit risk in our country. Many domestic scholars have reached that KMV model and CS model have strong adaptability in our country, respectively can reflect the credit risk information in the stock and bond markets. So now comes the questions, do the stock and bond markets reflect consistently for the same credit risk information? What is the connection between the two markets? Which market(or model) can reflect the credit risk information more timely and accurately? These questions are all basic issues in credit risk monitoring, and also the research focus of this paper.Applying KMV model and CS model, this paper firstly calculate the reciprocal of default distance(RDD) and credit spreads(CS) to respectively reflect the credit risk information in the stock and bond market, taking the listed companies which both issue shares and bonds as research samples. Then, from two time dimension—the long term and the short term, this paper studies the dynamic changes of RDD and CS, and the relationship between the actual credit risk, RDD and CS. In the research of long-term relationships, we use correlation analysis, and cointegration test to reach the conclusion that the stock market and bond market reflect consistently on credit risk information in the long term; And then, we use grouping statistics and regression analysis to verify that the company’s actual size of the credit risk is the key factor to affect the long-term consistency, that is, the greater the actual credit risk is, the stronger the consistency is. In the research of short term relationship, we use event study method, which has been improved, to study the short-term effects that some specific credit risk events(such as credit risk initial worsening, credit risk escalation, credit risk improving, etc.) have on RDD and CS. Some useful results are got. In the information effectiveness, the stock market can reflect the credit risk information better in a timely and effective manner, while there is a lag in corporate bond market, that is, the corporate bond market doesn’t reflect until the credit risk accumulate to a threshold value(about 6 months). While, with the increase of credit risk, the two markets tend to be more consistent. Based on the above research results, some reasonable suggestions are put forward for applying two models to establish suitable real-time monitoring system of credit risk in China.