基于遗传算法KMV模型的最优违约点确定  

Determination of KMV model′s optimal default point based on genetic algorithm

作　　者：冯敬海[1] 田婧[1] 

机构地区：[1]大连理工大学数学科学学院,辽宁大连116024

出　　处：《大连理工大学学报》2016年第2期181-184,共4页Journal of Dalian University of Technology

摘　　要：现代市场经济中资信评估具有重要作用,它起着社会监督和识别违约风险的作用.根据可获得的中国上市公司的基本数据,结合遗传算法对经典KMV模型中的最优违约点进行了重新定义.结果显示改进的模型拟合正确率比原模型高,即改进的KMV模型更适合应用于中国上市公司的资信状况评估.Credit evaluation plays an important role in modern market economy as the main force in the social supervision and risk identification of default.Based on the data of Chinese listing corporation,combined with genetic algorithm,the optimal default point in the classical KMV model is redefined.The applicable results indicate that the percentage of correctness of the improved model is higher than the original one,in other words,the improved KMV model is more suitable for application in China.

关 键 词：期权定价 KMV 遗传算法 信用风险 

分 类 号：F830.9[经济管理—金融学]