附加噪声长记忆过程的半参数估计方法研究

中国管理科学 ›› 2006, Vol. ›› Issue (4): 1-5.

• 论文 • 下一篇

附加噪声长记忆过程的半参数估计方法研究

赵巍, 何建敏

东南大学经济管理学院, 江苏, 南京, 210096

收稿日期:2005-09-25 修回日期:2006-07-07 出版日期:2006-08-28 发布日期:2012-03-07
基金资助:
国家自然科学基金资助项目(70371035)

Semi-Parametric Estimation Methods on Long-Memory Processes with Added Noise

ZHAO Wei, HE Jian-min

School of Economics & Management, Southeast University, Nanjing 210096, China

Received:2005-09-25 Revised:2006-07-07 Online:2006-08-28 Published:2012-03-07

摘要/Abstract

摘要： 附加噪声长记忆过程的参数估计在实证研究中一直受到回避.本文通过聚合算子对样本数据进行降噪处理,研究了局部Whittle(LW)估计和对数周期图(LP)回归两种半参数估计方法.结果表明LW估计方法相比LP回归,解决了半参数方法的参数选取问题,且能够完全忽略噪声数据的影响而得到一致的估计.将LW估计应用于中国股市,发现重大突发事件发生时的长记忆性表现得最为强烈,且事件后比事件前要强烈.

关键词: 长记忆, 聚合算子, LP回归, LW估计, 重大突发事件

Abstract: The parameter estimation of long memory process with added noise is always ignored.In this work,after the sample data are aggregated,the methods of semi-parametric estimation including local Whittle estimation and log-periodogram regression are used.Compared to LP regression,LW estimation was proved to solve the parameter selection,and it also can neglect the impression of noise data.Then LW estimation was applied in China stock market.The results presented that long memory was found greater during the gravely outburst events,and which was stronger in the post-event than in the pre-event.

Key words: long memory, aggregation operator, LW estimation, gravely outburst events

中图分类号:

F830.91

赵巍, 何建敏. 附加噪声长记忆过程的半参数估计方法研究[J]. 中国管理科学, 2006, (4): 1-5.

ZHAO Wei, HE Jian-min. Semi-Parametric Estimation Methods on Long-Memory Processes with Added Noise[J]. Chinese Journal of Management Science, 2006, (4): 1-5.

参考文献

[1] Hurst H.E..Long-Term storage of reservoirs[J].Transaction of the American Society of Civil Engineers,1951,116:770-808.
[2] 张维,黄兴.沪深股市的R/S实证分析[J].系统工程,2001,19(1):1-5.
[3] Lo A.W..Long-term Memory in Stock Market Prices[J].Econometrica,1991,59(5):1279-313.
[4] Peng C.K.,Buldyrev S.V.,Goudberger A.L.,et al.Mosale organization of DNA nucleotides[J].Physical Review E,1994,49(2):1685-1689.
[5] 张永东.中国证券市场股票收益持久性的经验证据[J].管理工程学院,2003,4(17):64-68.
[6] 魏宇,黄登仕.中国股票市场波动持久性特征的DFA分析[J].中国管理科学,2004,4(12):12-19.
[7] Kantellhardt J.W..Detecting long-range correlation with detrended fluctuation analysis[J].Physica A,2001,295:441-454.
[8] Geweke J.,Porter-Hudak.The estimation and application of long memory time series model[J].Journal of Time Series Analysis,1983,(4):221-238.
[9] Robinson P.M..Gaussian semi parametric estimation of long range dependence[J].The Annals of Statistics,1995b,23:1630-1661.
[10] 苏卫东,张世英.多元长记忆SV模型及其在沪深股市的应用[J].管理科学学报,2004,7(1):38-44.
[11] Taqqu M.S.,Teverovsky V..Robustness of Whittle type estimators for time series with long-range dependence[J].Stochastic Model,1997,13:723-757.
[12] Bollerslev T.,Wright J.H..Semi parametric estimation of long memory volatility dependencies:the role of high frequency data[J].Journal of Econometrics,2000,98:81-106.
[13] Cajueiro D.O.,Tabak B.M.,Souza N.A..Periodic market closures and the long-range dependence phenomena in the Brazilian equity market[J].Physica A,2005,351:512-522.
[14] Tabak B.M.,Cajueiro D.O..The long-range dependence behavior of the term structure of interest rates in Japan[J].Physica A,2005,350:418-426.
[15] Han Y.W..Long memory volatiility dependency,temporal aggregation and the Korean currency crisis:the role of a high frequency Korean won(KPW)-US dollar($)exchange rate[J].Japan and the World Economy,2005,17:97-109.
[16] 张庆翠,王春峰.中国股市波动性和成交量共同的长期记忆性研究[J].管理科学学报,2005,8(2):38-45.
[17] 徐梅,张世英.基于小波变换的长记忆随机波动模型估计方法研究[J].中国管理科学,2006,14(1):7-14.
[18] Robinson P.M.,Herry M..Long and short memory conditional heteroskedasticity in estimating the long memory parameter on levers[J].Econometric Theory,1999,15:299-336.
[19] Ding Z.,Granger C.,Engle R.F..A long memory property of stock market returns and a new model[J].Empirical Finance,1993,1:83-106.
[20] Baillie R.T..Long memory processes,fractional integration in econometrics[J].Journal of Econometrics,1996,73:5-59.
[21] Breidt F.J.,et al.The detection,estimation of long memory in stochastic volatilty[J].Journal of Econometrics,1998,83:325-348.
[22] Taqqu M.S.,Teverovsky V..A practical guide to the heavy tails:statistics techniques and applications[M].Birkhauser,Boston,1998:177-217.
[23] Tele P.,Wei W.W.S.,Crato N..The use of aggregate time series in testing for long memory[R].Bulletin of the International Statistics Institute,52nd Session,1999:341-342.

附加噪声长记忆过程的半参数估计方法研究

Semi-Parametric Estimation Methods on Long-Memory Processes with Added Noise

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 10

Metrics

本文评价

推荐阅读 10

[1]	吴鑫育, 李心丹, 马超群. 双因子非对称已实现SV模型及其实证研究[J]. 中国管理科学, 2018, 26(2): 1-13.
[2]	周伟杰, 党耀国, 顾荣宝. 基于灰色算子的分形法及应用[J]. 中国管理科学, 2017, 25(10): 89-99.
[3]	李云红, 魏宇, 张帮正. 股票市场历史信息的长记忆性特征研究[J]. 中国管理科学, 2015, 23(9): 37-45.
[4]	刘志东, 刘雯宇. Lévy过程驱动的非高斯OU随机波动模型及其贝叶斯参数统计推断方法研究[J]. 中国管理科学, 2015, 23(8): 1-9.
[5]	曹广喜, 曹杰, 徐龙炳. 双长记忆GARCH族模型的预测能力比较研究——基于沪深股市数据的实证分析 [J]. 中国管理科学, 2012, (2): 41-49.
[6]	何建敏, 赵巍. 股市波动长记忆性聚合效应的半参数检验[J]. 中国管理科学, 2008, 16(4): 12-17.
[7]	余俊, 方爱丽, 熊文海. 国际股票市场收益的长记忆性比较研究[J]. 中国管理科学, 2008, 16(4): 24-29.
[8]	耿克红, 张世英. 中国股市超高频持续期序列长记忆性研究[J]. 中国管理科学, 2008, 16(2): 7-13.
[9]	许友传, 何佳. 长期冲击、价格调整与股票组合收益的互相关关系[J]. 中国管理科学, 2007, 15(4): 9-13.
[10]	刘金全, 李庆华, 郑挺国. 具有平滑迁移的ARFIMA模型及其应用[J]. 中国管理科学, 2007, 15(3): 6-13.