基于ARFIMA模型的钢材价格预测研究  

Research on Steel Price Forecasting Based on ARFIMA Model

作　　者：陈雪 申建红 徐文慧 朱琛 CHEN Xue;SHEN Jianhong;XU Wenhui;ZHU Chen(School of Management Engineering,Qingdao University of Technology,Qingdao,Shandong 266520,China;University Research Center for Smart City Construction and Management of Shandong Province,Qingdao,Shandong 266520,China)

机构地区：[1]青岛理工大学管理工程学院,山东青岛266520 [2]山东省高校智慧城市建设管理研究中心,山东青岛266520

出　　处：《河北工程大学学报（自然科学版）》2020年第3期64-68,共5页Journal of Hebei University of Engineering:Natural Science Edition

基　　金：国家自然科学基金资助项目(71471094)。

摘　　要：钢材价格的准确预测有利于施工企业拟定合理的材料采购策略。针对当前钢材价格的预测研究中均未考虑其价格变动的长记忆性,导致建模过程中有效信息丢失,预测误差增大。建立了考虑长记忆性的ARFIMA钢材价格预测模型,以青岛市2014年1月到2019年6月螺纹钢的价格为研究对象进行了钢材价格预测,并利用ARFIMA模型和ARIMA模型的预测值与真实值进行对比分析,实验结果显示:ARFIMA模型较ARIMA模型的钢材价格预测精准度提高了1.7%,且预测效果更稳定。The accurate prediction of steel prices is helpful for construction companies to formulate reasonable material procurement strategies.For the current steel price prediction research,the long memory of its price changes is not considered,resulting in the loss of effective information in the modeling process and the increase of prediction errors.In this paper,the ARFIMA steel price prediction model considering long memory was established.The steel price prediction was carried out based on the price of rebar in Qingdao from January 2014 to June 2019.The predicted values of the ARFIMA model and ARIMA model were used for comparative analysis of the true value.The experimental results show that the accuracy of the steel price prediction of the ARFIMA model is 1.7%higher than that of the ARIMA model,and the prediction effect is more stable.

关 键 词：钢材价格预测 ARFIMA模型 时间序列 长记忆性 

分 类 号：TU511.3+3[建筑科学—建筑技术科学]