{"title":"Research on stock price forecast based on gray relational analysis and ARMAX model","authors":"Chui-yong Zheng, Jun Zhu","doi":"10.1109/GSIS.2017.8077689","DOIUrl":null,"url":null,"abstract":"There are some uncertainties associated with the influencing factors in the stock price forecasting model. Main influencing factors of stock price are selected by gray relational analysis, and the main influencing factor was used as an exogenous variable to establish the ARMAX model to forecast the stock price. Taking PetroChina as an example to carry out case analysis, the result shows that the fitting between the stock price forecast and the actual value calculated by the ARMAX model is high. This paper effectively improves the accuracy of stock price forecasting while providing a valuable reference for investors.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GSIS.2017.8077689","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
There are some uncertainties associated with the influencing factors in the stock price forecasting model. Main influencing factors of stock price are selected by gray relational analysis, and the main influencing factor was used as an exogenous variable to establish the ARMAX model to forecast the stock price. Taking PetroChina as an example to carry out case analysis, the result shows that the fitting between the stock price forecast and the actual value calculated by the ARMAX model is high. This paper effectively improves the accuracy of stock price forecasting while providing a valuable reference for investors.