Stock price analysis based on the research of multiple linear regression macroeconomic variables

被引：1

作者：

Wang, Fei ^{[1
]}

Chen, Wanling ^{[2
]}

Fakieh, Bahjat ^{[3
]}

Alhamami, Mohammed Alaa ^{[4
]}

机构：

[1] Guangzhou Xinhua Univ, Guangzhou 510520, Peoples R China

[2] Guangdong Univ Foreign Studies, Res Ctr Int Trade & Econ, Guangzhou 510006, Peoples R China

[3] King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Informat Syst, Jeddah, Saudi Arabia

[4] Appl Sci Univ, Al Eker, Bahrain

来源：

APPLIED MATHEMATICS AND NONLINEAR SCIENCES | 2022年 / 7卷 / 01期

关键词：

multiple linear regression; macroeconomic variables; listed companies; financial performance; stock prices;

D O I：

10.2478/amns.2021.2.00097

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The article uses SPSS statistical analysis software to establish a multiple linear regression model of short-term stock price changes of domestic agricultural listed companies. The article uses a stable time series based on the ARMA model for stable agricultural value-added, fiscal expenditure and market interest rates. The regression method is used to study its impact on the stock price index. Compared with the existing stock forecasting methods, this method has simple data collection and no specific requirements for data selection, and the prediction results have a high degree of fit. Therefore, this method is suitable for most stocks.

引用

页码：267 / 274

页数：8

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