Calculation Of The KMV Model’s Optimal Default Point According To Genetic Algorithms

In modern financial market, credit evaluation plays an important role, as the main force in the social supervision of power, the economic impact is self-evident, and therefore we have the necessity to establish China’s credit system. Based on the stock market data, the KMV model can directly monitor the credit risk. Also, it has important effects on the Chinese market researching. Because the ownership structure of China’s listing Corporation has its own unique, we must adjust the method on the basis of the model, In this paper, based on the data of Chinese listing Corporation, combined with genetic algorithm we redefine the optimal default point in the classical KMV model. We found that the improved KMV model is more suitable for Chinese. The results indicate that the percentage of correctness of the improved model is higher than the original model, in other words, the improved KMV model is more suitable for application in China. Moreover, it can help us to predict the default of listing Corporation.