Application of Python in Data Forecasting using SARIMA Models

Vesela Dimitrova
University of National and World Economy, Sofia (Bulgaria)

https://doi.org/10.53656/math2025-6-2-apd

Abstract. This study aims to build and estimate a SARIMA model to predict the prices of the shares of a company listed on NYSE. With the help of Python, the daily closing prices of the stock for the period from 3.01.2023 to 17.03.2025 were taken. Also, SARIMA models were evaluated and code was compiled to select the most appropriate parameters. Finally, the daily forecasts for one month were calculated. The study found that SARIMA model can be considered reliable for forecasting stock prices and can complement any other analysis method. Future research could also include enhancing the study with external factors and improving the forecasts could be also done by testing of SARIMAX models.
Keywords: Python, forecasting, econometric modelling, SARIMA, financial markets

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