Prediction of Weekly Stock Price of PT Indofood CBP Sukses Makmur Tbk (ICBP) with ARIMA Box-Jenkins Method

Putri Felicia

Abstract


This research aims to forecast the weekly stock prices of PT Indofood CBP Sukses Makmur Tbk (ICBP) using the ARIMA model based on the Box-Jenkins methodology. Weekly closing price data from January 1 2024 to January 26 2025 is utilized as the basis for analysis. The data is first tested for stationarity, and appropriate differencing is applied to stabilize the mean. The ARIMA(2,1,0) model is identified as the best-fitting model. Model diagnostics, including the Ljung-Box test, confirm that the residuals exhibit white noise characteristics, indicating a good model fit. Forecasting performance is assessed using the Mean Absolute Percentage Error (MAPE), which resulted in a value of 1.58%, suggesting a high level of forecasting accuracy. The findings demonstrate that the ARIMA model is effective for short-term stock price prediction and can serve as a useful tool for investors and financial analysis. 

Full Text:

PDF

References


G. E. P. Box, G. M. Jenkins, G. C. Reinsel, and G. M. Ljung, Time Series Analysis: Forecasting and Control, 5th ed. Hoboken, NJ: Wiley, 2015.

S. D. Laskarjati and I. S. Ahmad, “Perbandingan Peramalan Harga Saham menggunakan Autoregressive Integrated Moving Average (ARIMA) dan Fuzzy Time Series Markov Chain (Studi Kasus: Saham PT Indofood CBP Sukses Makmur Tbk),” J. Sains dan Seni ITS, vol. 11, no. 6, pp. 397–404, 2022.

R. T. Dewanti, E. Zukhronah, and W. Sulandari, “Peramalan Harga Saham PT Indofood Sukses Makmur Tbk Menggunakan Model Hibrida Singular Spectrum Analysis (SSA) – Autoregressive Integrated Moving Average (ARIMA),” J. Gaussian, vol. 13, no. 2, pp. 270–279, 2024.

Investing.com, “PT Indofood CBP Sukses Makmur Tbk [ICBP] Historical Data,” 2024.

A. I. S. Wardhani and M. R. Yudhanegara, "Forecasting Weekly Stock Price of PT. Aneka Tambang Tbk (ANTM) Using ARIMA Box-Jenkins Method," Journal of Actuarial, Finance and Risk Management (JAFRM), vol. 3, no. 2, pp. –, Dec. 2024

R. J. Hyndman and G. Athanasopoulos, Forecasting: Principles and Practice, 3rd ed. Melbourne, Australia: OTexts, 2021.

C. D. Lewis, Industrial and business forecasting methods: A Radical guide to exponential smoothing and curve fitting. London: Butterworth Scientific, 1982.

H. Wickham and G. Grolemund, R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. Sebastopol, CA, USA: O'Reilly Media, 2017.

H. Akaike, “A new look at the statistical model identification,” IEEE Trans. Automat. Control, vol. 19, no. 6, pp. 716–723, Dec. 1974

S. S. Shapiro and M. B. Wilk, “An analysis of variance test for normality (complete samples),” Biometrika, vol. 52, no. 3–4, pp. 591–611, Dec. 1965.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Editorial Office:

President University Actuarial Science: Jalan Ki Hajar Dewantara, Mekarmukti, Cikarang Utara, Bekasi 17530