Improving estimation of the fractionally differencing parameter in the SARFIMA model using tapered periodogram

被引:1
|
作者
Ye, Xunyu [1 ]
Gao, Ping [1 ]
Li, Handong [1 ]
机构
[1] Beijing Normal Univ, Dept Management Sci & Engn, Haidian Dist, Peoples R China
关键词
Long memory models; Seasonality; Tapered periodogram; Monte Carlo study; Intraday volume; High-frequency volatility; LONG-MEMORY MODEL; BANDWIDTH;
D O I
10.1016/j.econmod.2014.11.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper presents a new method to estimate the fractional differencing parameters in the SARFIIVIA model. A technique of split cosine bell tapering is suggested to improve the EGPH method. The simulation study shows that the optimal split proportion and bandwidth for the EGPH with split cosine bell tapering method respectively are p = 0.1 and LI = 0.9. The new method with the optimal parameters outperforms the EGPH and EGPH with cosine bell tapering. We further applied the EGPH method to estimate intraday volume series and high-frequency absolute return data. The results show that the seasonal fractionally differencing parameters are all estimated to be large, while the nonseasonal fractionally differencing parameters are all very small. This indicates that their long memory property may be mainly caused by the structure of long-range dependence at the seasonal lags instead of dependence at the nonseasonal lags. (c) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:167 / 179
页数:13
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