Predicting Stock Market Trends with ARIMA: A Data-Centric Approach to the BSE Index
Year: 2025
Type: article
Abstract: Stock market volatility makes accurate forecasting vital for informed trading decisions and profit maximization. Over the years, various models have been introduced to enhance the reliability of time series predictions. This study applies the ARIMA model to evaluate data stability and forecast movements in the BSE Index. Model selection was guided by statistical measures including SIGMASQ, Adjusted R², AIC, and BIC, with ARIMA (2,1,2) emerging as the most suitable specification. Using monthly data from January 2021 to January 2025 (49 observations), the model generated forecasts for February 2025 through December 2025, yielding 11 projected values. The results highlight ARIMA’s effectiveness as a short-term forecasting tool, offering actionable insights for informed investment decisions.
Authors: Kalyan Kumar Bethu, Dr.M.Sravani
Institution: Krishna University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7084026407
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