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FIGARCH模型对股市收益长记忆性的实证分析
引用本文:汤果,何晓群,顾岚. FIGARCH模型对股市收益长记忆性的实证分析[J]. 统计研究, 1999, 16(7): 39-42
作者姓名:汤果  何晓群  顾岚
作者单位:中国人民大学统计系(汤果,顾岚),中国人民大学统计系数理统计教研室(何晓群)
摘    要:一、问题的提出长记忆性是指过去的冲击持续到将来,对预期的将来具有很大的影响。在大多数情况下,自相关函数的曲线图用来描述时间序列的长记忆特征。因此长记忆性可以定义如下:假设Yt是一个离散的时间序列,j阶滞后的自相关函数为ρj,如果有limn→∞Σnj=...

关 键 词:FIGARCH(p.d.q)模型  长记忆性  

Case Study on the Long Memory of FIGARCH Model on Stock Revenue
Tang guo,He Xiaoqun,Gu Lan. Case Study on the Long Memory of FIGARCH Model on Stock Revenue[J]. Statistical Research, 1999, 16(7): 39-42
Authors:Tang guo  He Xiaoqun  Gu Lan
Abstract:The purpose of this paper is to represent and model the long memory property of Chinese stock returns series and compare it with foreign stock returns. The basic definition of long memory and FIGARCH model are given firstly, a Quasi-Maximum Likelihood Estimation (QMLE) and mixed algorithm are also applied. Through Monte-Carlo simulation, some of the most important results are reported. Then we compare the GRACH and IGARCH with FIGARCH processes, choose the one that best fit for the return series of Shanghai stock market and New York stock market respectively. The same aspect and the difference between these two market are analyzed, and some reasons are given.
Keywords:
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