计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (12): 23-26.DOI: 10.3778/j.issn.1002-8331.2009.12.007

• 博士论坛 • 上一篇    下一篇

ARFIMA-EGARCH-M模型在汇率收益率波动分析中的应用

杨瑞成1,2,秦学志2   

  1. 1.鲁东大学 数学与信息学院,山东 烟台 264025
    2.大连理工大学 管理学院 管理科学与工程博士后流动站,辽宁 大连 116024
  • 收稿日期:2008-12-29 修回日期:2009-02-04 出版日期:2009-04-21 发布日期:2009-04-21
  • 通讯作者: 杨瑞成

Volatility analysis of return of exchange rate using ARFIMA-EGARCH-M model

YANG Rui-cheng1,2,QIN Xue-zhi2   

  1. 1.School of Mathematics and Information,Ludong University,Yantai,Shandong 264025,China
    2.Postdoctor Working Station of School of Management Science and Engineering,Dalian University of Technology,Dalian,Liaoning 116024,China
  • Received:2008-12-29 Revised:2009-02-04 Online:2009-04-21 Published:2009-04-21
  • Contact: YANG Rui-cheng

摘要: 为了解决汇率收益率波动中的“尖峰厚尾”、中期记忆和非对称特征,提出了利用ARFIMA-EGARCH-M模型建立汇率收益率波动模型。以人民币/欧元的日汇率数据为例,在误差分布分别为正态分布、T分布、GED分布与SKT分布的前提下分别进行模型拟合分析,得出基于GED分布的ARFIMA(1,d,1)-EGARCH(2,2)-M模型拟合人民币/欧元汇率收益率效果最好,能较好地解决“尖峰厚尾”、中期记忆和非对称现象。

关键词: ARFIMA-EGARCH-M模型, 尖峰厚尾, 中期记忆, 非对称

Abstract: To solve the higher peak and fat tail phenomenon,immediate memory and asymmetric features,this paper formulate the volatility model of exchange rate returns using the ARFIMA-EGARCH-M model.Based on the example on the return sequences of CNY/EUR exchange rate,assuming the error sequence is Normal distribution,T distribution,GED distribution and SKT distribution respectively,authors derive that the ARFIMA(1,d,1)-EGARCH(2,2)-M with GED distribution can better solve the higher peak and fat tail,immediate memory and asymmetric features.

Key words: ARFIMA-EGARCH-M model, higher peak and fat tail, immediate memory, asymmetric characterization