文章摘要
冯敬海,田婧.基于遗传算法KMV模型的最优违约点确定[J].,2016,56(2):181-184
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
  
DOI:10.7511/dllgxb201602011
中文关键词: 期权定价  KMV  遗传算法  信用风险
英文关键词: option pricing  KMV  genetic algorithm  credit risk
基金项目:
作者单位
冯敬海,田婧  
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中文摘要:
      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.
英文摘要:
      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.
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