计算机科学 ›› 2017, Vol. 44 ›› Issue (Z11): 61-64.doi: 10.11896/j.issn.1002-137X.2017.11A.011

• 智能计算 • 上一篇    下一篇

基于多元线性回归的螺纹钢价格分析及预测模型

陈海鹏,卢旭旺,申铉京,杨英卓   

  1. 吉林大学计算机科学与技术学院 长春130012,吉林大学软件学院 长春130012,吉林大学计算机科学与技术学院 长春130012,吉林大学软件学院 长春130012
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家青年科学基金项目(61305046,3),吉林省自然科学基金项目(20140101193JC)资助

Analysis and Prediction on Rebar Price Based on Multiple Linear Regression Model

CHEN Hai-peng, LU Xu-wang, SHEN Xuan-jing and YANG Ying-zhuo   

  • Online:2018-12-01 Published:2018-12-01

摘要: 通过分析期货黑色系品种螺纹钢产业链上下游的关系,提出了一种基于多元线性回归分析的螺纹钢价格分析及预测模型。首先,收集 影响螺纹钢价格的主要因素数据,包括焦炭期货结算价、焦煤期货结算价、铁矿石期货结算价、热卷期货结算价与人民币兑美元汇率中间价;然后,通过散点图与趋势线对这些影响因素进行分析以确定影响因素,借助SPSS与NCSS软件利用收集到的数据构建基于最小二乘法的多元线性回归模型,并通过岭回归分析消除自变量间的共线性,得到修正后的模型;最后,运用此模型对未来一个月交易日的螺纹钢价格进行较为精准的预测。实验表明,该模型拟合度较高,具有一定的实用性。

关键词: 多元线性回归,螺纹钢价格,最小二乘法,岭回归

Abstract: A kind of rebar price analysis as well as prediction model based on multiple linear regression analysis was proposed by means of analyzing the upstream and downstream relationship of rebar industrial chain in futures black line variety.Firstly,the data of major factors influencing rebar price is collected,including coke futures settlement price,coking coal futures settlement price,iron ore futures settlement price,hot rolled futures settlement price,and central parity rate of RMB to USD.Later,these influencing factors are analyzed through scatter diagram and rend line to determine influencing factors.The multiple linear regression model based on least square method is constructed by virtue of SPSS and NCSS,and the collected data.Meanwhile,the collinearity among independent variables are moved through ridge regression to obtain revised model.At last,this model is applied to carry out accurate prediction of rebar price on trade day in the next month.The experiment indicates that the fitting degree of this model is higher with certain practicability.

Key words: Multiple linear regression,Rebar price,Least-square method,Ridge regression

[1] 刘金山,王晓晓.中外螺纹钢期现价格互动效用研究[J].商业研究,2015(1):8-14.
[2] 马刚,马丽.我国钢材期货价格、现货价格关系实证研究——基于螺纹钢期货市场与现货市场数据[J].中国证券期货,2010(8):27-29.
[3] 刘任帆,陈芳舒.我国钢材期货与现货市场的互动性探究——基于上海螺纹钢的实证研究[J].杭州电子科技大学学报(社会科学版),2011(3):13-17.
[4] 王立民,兴长宇,刘祥东,等.基于EMD分解的螺纹钢期货价格发现的实证研究[J].科技和产业,2012,12(8):78-82.
[5] 李静晶.我国螺纹钢期货价格与现货价格研究[J].金融经济(理论版),2016(3):149-151.
[6] 成月.宏观经济因素对我国螺纹钢期货价格的影响研究——基于VEC模型的实证分析[J].市场论坛,2016(6):20-23.
[7] UYANLK G K,GLER N,et al.A Study on Multiple Linear Regression Analysis[J].Procedia-Social and Behavioral Scien-ces,2013,106(106):234-240.
[8] MARCHIONNI V,LOPES N,MAMOUROS L,et al.Modelling Sewer Systems Costs with Multiple Linear Regression[J].Water Resources Management,2014,28(13):4415-4431.
[9] LIU H H,JI W L,ZHANG P,et al.The Research of Wine Quality Evaluation Based on Multiple Linear Regression[J].Advanced Materials Research,2013,756-759:2489-2493.
[10] 崔江龙.多元回归分析在能源利用中的应用[J].商,2015(49):68.
[11] 付倩娆.基于多元线性回归的雾霾预测方法研究[J].计算机科学,2016,43(s1):526-528.
[12] 陈玲燕.多重共线性下的线性回归方法综述[J].现代农业,2008(5):67-69.
[13] HOERL A E,KENNARD R W.Ridge regression:biased estimation for nonorthogonal problems[J].Technometrics,1970,42(1):80-86.
[14] 张丹平.基于岭回归方法的我国能源消费影响因素研究[J].统计与决策,2012(21):146-148.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!