Forecasting Weekly Stock Price of PT. Bank Negara Indonesia Tbk (BBNI) Using ARIMA Box-Jenkins Method

Nazwa Indry Chintya

Abstract


Dynamic stock price movements in the economic world demand the ability to predict future trends, especially for investors and companies that make strategic decisions. This research focuses on forecasting the weekly stock price of PT Bank Negara Indonesia Tbk (BBNI) using the Autoregressive Integrated Moving Average (ARIMA) method based on the Box-Jenkins approach. The data analyzed consists of weekly closing prices from January 6, 2024 to November 2, 2024 as many as 44 observations. The results show that the ARIMA (2,1,0) model is the best fit for this dataset, with relatively highly accurate prediction results, as indicated by a Mean Absolute Percentage Error (MAPE) of 4.09%. These results offer valuable insights to help investors and companies anticipate stock price changes, supporting more informed and strategic investment planning.

Keywords


ARIMA; Forecasting: BBNI; Stock price; Time series.

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