区间型金融时间序列的长记忆性研究  

Long Memory Study of Interval Financial Time Series

作　　者：丁勤祥 王哲 王艺宁 李铭源 DING Qin-xiang;WANG Zhe;WANG Yi-ning;LI Ming-yuan(School of Economics,Anhui University,Hefei 230601,China;School of Mathematical Sciences,Anhui University,Hefei 230601,China)

机构地区：[1]安徽大学经济学院,合肥230601 [2]安徽大学数学科学学院,合肥230601

出　　处：《重庆工商大学学报（自然科学版）》2020年第1期104-111,共8页Journal of Chongqing Technology and Business University:Natural Science Edition

基　　金：安徽大学大学生创新创业训练计划(201710357455;201810357203;201810357206;201810357518;201810357519)

摘　　要：研究金融时序的长记忆性能够帮助人们更加准确地刻画金融市场的特征,而在现有研究中,有关区间型金融时序长记忆性的研究很少。因此,考虑了区间型金融时序蕴含的长记忆性特征及其基于现有实值金融时序长记忆性建模的区间值时序预测模型,首先,将区间数表示成区间中心和区间半径的形式;然后分别对中心和半径序列进行长记忆性检验,并对具有长记忆性的序列进行组合预测;最后,以上证综指和深证综指的区间股指为实证对象进行验证。实证结果表明:上证综指的区间股指具有明显的长记忆性,且组合预测能够显著提高区间型金融时序的预测精度。Studying the long memory of financial time series can help people characterize financial markets accurately. However,studies on the interval financial time series are fewer. Therefore,the long-memory features of interval-based financial time series and its interval time series prediction model based on existing point-valued financial time series long memory modeling are considered in this paper. Firstly,the interval number is expressed as the interval center and the interval radius. Then,the center series and radius series are tested respectively whether they have long memory,and the interval-combination forecast model is proposed to predict the series which has long memory. Finally,an example about Shanghai Composite Index and Shenzhen Component Index is given to show that the interval stock index of Shanghai Composite Index has long memory,and the interval combination forecasting model can improve the prediction accuracy of interval financial time series.

关 键 词：区间金融时序 长记忆性 HURST指数 

分 类 号：O221.1[理学—运筹学与控制论]