Exploring Long-Memory Process in the Prediction of Interval-Valued Financial Time Series and Its Application

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外文摘要：Long-memory process has been widely studied in classical financial time series analysis,which has merely been reported in the field of interval-valued financial time series.The aim of this paper is to explore long-memory process in the prediction of interval-valued time series(IvTS).To model the long-memory process,two novel interval-valued time series prediction models named as interval-valued vector autoregressive fractionally integrated moving average(IV-VARFIMA)and ARFIMAX-FIGARCH were established.In the developed long-memory pattern,both of the short term and long-term influences contained in IvTS can be included.As an application of the proposed models,interval-valued form of WTI crude oil futures price series is predicted.Compared to current IvTS prediction models,IV-VARFIMA and ARFIMAX-FIGARCH can provide better in-sample and out-of-sample forecasts.

外文关键词：

ARFIMAX-FIGARCHinterval-valued time seriesIV-VARFIMAlong-memory processWTI crude oil futures price

作者：

SHEN Tingting、TAO Zhifu、CHEN Huayou

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作者单位：

School of Economics,Anhui University,Hefei 230601,China

Center for Financial and Statistical Research,Anhui University,Hefei 230061,China

Stony Brook Institute at Anhui University,Anhui University,Hefei 230601,China

Center for Applied Math-ematics,Anhui University,Hefei 230601,China

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基金：

Humanities and Social Sciences Research Youth Project of the Ministry of Education of China安徽省自然科学基金安徽省自然科学基金安徽省自然科学基金安徽省自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金Provincial Natural Science Research Project of Anhui Colleges,Chinateacher project of Anhui Ecology and Economic Development Research Center in(2021)

项目编号：

21YJCZH1482108085MG2392108085QG2902008085QG3342008085MG226720010017190100172071001KJ2020A0004AHST2021002

出版年：

2024

DOI：

10.1007/s11424-024-2112-9

系统科学与复杂性学报(英文版)

中国科学院系统科学研究所

系统科学与复杂性学报(英文版)

影响因子：0.181

ISSN：1009-6124

年,卷(期)：2024.37(2)

参考文献量45