<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</abstract>

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.

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

Research Center for International Trade and Economics

Department of Information System, Faculty of Computing and Information Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The article uses SPSS statistical analysis software to establish a multiple linear regression model of short-term stock price changes of domestic agricultural...

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

Online veröffentlicht: 22. Nov. 2021

Seitenbereich: 267 - 274

Eingereicht: 17. Juni 2021

Akzeptiert: 24. Sept. 2021

DOI: https://doi.org/10.2478/amns.2021.2.00097

Schlüsselwörter
multiple linear regression, macroeconomic variables, listed companies, financial performance, stock prices

© 2021 Fei Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Online veröffentlicht: 22. Nov. 2021

Seitenbereich: 267 - 274

Eingereicht: 17. Juni 2021

Akzeptiert: 24. Sept. 2021

DOI: https://doi.org/10.2478/amns.2021.2.00097

Schlüsselwörtermultiple linear regression, macroeconomic variables, listed companies, financial performance, stock prices

© 2021 Fei Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
multiple linear regression, macroeconomic variables, listed companies, financial performance, stock prices