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

• Autores: Fei Wang, Wanling Chen, Bahjat Fakieh, Basel Jamal Ali
• Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 7, Nº. 1, 2022, págs. 267-274
• Idioma: inglés
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• Resumen

  • The article uses SPSS statistical analysis software to establish a multiple linear regression model of short-term stock pricechanges of domestic agricultural listed companies. The article uses a stable time series based on the ARMA model forstable agricultural value-added, fiscal expenditure and market interest rates. The regression method is used to study itsimpact on the stock price index. Compared with the existing stock forecasting methods, this method has simple datacollection 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