Analysis of Closing Price Forecasts for PT Bank Mandiri (Persero) Tbk (BMRI) Stock Using the Multiple Linear Regression Method Based on OHLCV Data - Dostri Ambarita; Rony Genevent Marpaung; Juan Prihanda Nainggolan (Journal Of Management Analytical and Solution (JoMAS), 2026)
This study aims to analyze and predict the closing stock price of PT Bank Mandiri (Persero) Tbk (BMRI) using multiple linear regression based on OHLCV (Open, High, Low, Close, Volume) data. The data used in this research is secondary data obtained from historical stock price records over a specific period. The independent variables in this study include Open, High, Low, and Volume, while the dependent variable is the closing price. The analysis method applied is Ordinary Least Squares (OLS) to estimate the regression model parameters. The results show that the High and Low variables have a significant influence on the closing price, while Volume has a relatively weaker effect. The model evaluation using R-squared indicates a strong explanatory power, suggesting that the regression model is capable of explaining most of the variation in the closing price. This study provides insights into the relationship between OHLCV variables and stock prices, which can be useful for investors in making data-driven decisions.