摘要
文章借鉴Charles(2005)提出的GARCH模型异常值检测法,提出一种GARCH模型AO型与IO型异常值稳健检测法,模拟不同污染率、不同样本量下的GARCH序列。实证检验结果显示,稳健检测法对异常值检测的正确率显著高于传统检测法。
This paper uses for reference GARCH model outlier detection method proposed by Charles(2005),proposes a robust GARCH model AO and IO outlier detection method,and simulates GARCH sequences with different pollution rates and different sample sizes.The result of empirical test shows that the accuracy of the proposed robust detection model is significantly higher than that of traditional detection.
作者
王志坚
Wang Zhijian(Big Data&Educational Statistics Application Laboratory,Guangdong University of Finance&Economics,Guangzhou 510032,China;School of Statistics and Mathematics,Guangdong University of Finance&Economics,Guangzhou 510032,China)
出处
《统计与决策》
CSSCI
北大核心
2020年第10期41-44,共4页
Statistics & Decision
基金
广东省普通高校特色创新类项目(2019KTSCX042)。