Credit Risk Assessment Of Chinese Listed Firms Basing On KMV Model

Credit risk measurement is becoming increasingly important in today's society, however, most traditional credit risk measurement models are based on financial accounting data, with the "looking back" feature, but KMV model, because of its advantage of basing on stock market data and "looking forward" feature, has received wide international attention in recent years.Different from other author choosing only pairs of ST companies and good companies as samples, this paper randomly selected stock market data, then screen them according to their integrity and abnormal results, finally we gets the sample data. By using the Black-Scholes Option Pricing Model and doing some unusual adjustments of the input variables of KMV model, such as using the growth-rate of assets in three years instead of the growth-rate of equity market value, and annual risk-free interest rate attained by way of time-weighted average etc, then through playing program in MATLAB 7, the iterative process is carried out and KMV model results-Distance to Default(DD)-are obtained, the larger DD is, the smaller the risk of default is. Meanwhile, by comparison with the traditional model of Z-score based on the financial data, I noticed that DD changes in the same way with the Z-score model only on a single stock condition, when districting risk of default between different stocks, it does not do a good job. For example, normal firm's DD is lower than ST firms', However, Z-score model can properly reflect the company's Z-score difference. This is probably because some normal stock's equity-volatility is too large, and KMV model's many parameters and input variables are not yet unified, a dominant fixed formula was not published, therefore, KMV model can only generally distinguish the size of the risk of default between different stocks, its effectiveness is still less favorable than the Z-score model, but as more improvement of the accounting standards and other market mechanisms in China, I believe KMV model will be widely used and demonstrate its superiority.Finally, the yearly DD span too large, and cannot dynamically reflect the Risk of default of firms. As of this, this paper calculate the quarterly DD of three stocks from 2006 to 2009, and the results display that quarterly DD could reflect the dynamic changes of the default risk of the process more subtly. Meanwhile, analysis showed that the three stocks'DD has all the same overall trend, indicating that quarterly DD does indeed show the dynamic change of the default risk of the process. I also found that the overall changing trend of the DD is roughly opposite to the changing trend of Shanghai Composite Index, but this is just a guess which needs to be validated.