摘要
基于模糊数学和模糊时间序列分析理论,在模糊GARCH与GJR-GARCH模型的基础上建立模糊GJR-GARCH模型,并用遗传算法估计了该模型的参数。实证发现沪深两市的收益波动率具有明显的非对称性,相对于普通的GARCH、GJR-GARCH和模糊GARCH模型,模糊GJR-GARCH模型能更好的处理收益率的波动群聚性、时变性和非对称性,具有更好的估计精度。
Based on fuzzy mathematics and fuzzy time series analysis theory,Fuzzy GJR-GARCH model is established by combing Fuzzy GARCH and GJR-GARCH model,the parameters are estimated by genetic algorithm.We found obvious asymmetry in the volatility of return in Shanghai and Shenzhen stock markets.Comparison with GARCH,GJR-GARCH and Fuzzy GARCH model,Fuzzy GJR-GARCH model can obtain good estimation results and describe the clustering,time-varying and asymmetry better.
出处
《数理统计与管理》
CSSCI
北大核心
2014年第3期559-570,共12页
Journal of Applied Statistics and Management
基金
国家自然科学基金项目(71101118)
教育部新世纪优秀人才支持计划(NCET-13-0961)
中央高校基本科研业务费专项资金资助项目(JBK131118、JBK120405)资助
