KUMAL

WEBKUMAL

The Application of ARIMA Box-Jenkins Method for Forecasting the Weekly Stock Price of PT. Telkom Indonesia Tbk | Sumbayak | Proceeding of The Symposium on Data Science (SDS)

The Application of ARIMA Box-Jenkins Method for Forecasting the Weekly Stock Price of PT. Telkom Indonesia Tbk

Angelique Melinda Rohsinarni Sumbayak

Abstract


The stock is one of the most popular financial market instruments. Conversely, because stocks offer an enticing level of profit, many investors prefer them as an investment. Nonetheless, stocks are a well-liked investment choice among investors due to their potential for earning huge profits. In this work, we will forecast the weekly stock prices of PT. Telkom Indonesia Tbk (TLKM.JK) for 5 weeks from March 4, 2024 to April 1, 2024. The Autoregressive Integrated Moving Average (ARIMA) method is a valuable tool for investors to utilize when forecasting the stock and making purchase choices. We use the historical weekly stock price data for PT. Telkom Indonesia Tbk (TLKM.JK) from February 27, 2023 to February 26, 2024 was collected from Yahoo Finance website to create a forecast. In this study, there’s 4 different ARIMA models, the analysis show that the ARIMA (1,2,1) is the best model

Keywords


ARIMA; time series;forecasting; stock; PT. Telkom Indonesia Tbk

Full Text:

PDF

References


C.-F. Tsai and S.-P. Wang, "Stock Price Forecasting by Hybrid Machine Learning Techniques," International MultiConference of Engineers and Computer Scientists, vol. 1, 2009.

"PT Telkom Indonesia Tbk - Historical Stock Price Data," Yahoo Finance, [Online]. Available: https://finance.yahoo.com/quote/TLKM.JK/history?frequency=1wk.

"Profil dan Riwayat Singkat," [Online]. Available: https://www.telkom.co.id/sites/about-telkom/id_ID/page/profil-dan-riwayat-singkat-22.

E. G. Manurung and E. S. Nugraha, "Forecasting the Weekly Stock Price of PT. OCBC NISP Tbk. using Auto Regressive Integrated Moving Average," Journal of Actuarial, Finance and Risk Management, 2023.

A. Olivia and E. S. Nugraha, "Forecasting PT Bank Central Asia Tbk Stock Price Using ARIMA," Journal of Actuarial, Finance and Risk Management, 2023.

P. Mondal, L. Shit and S. Goswami, "Study of Effectiveness of Time Series Modeling (ARIMA) In Forecasting Stock Prices," International Journal of Computer Science, Engineering and Applications (IJCSEA), vol. 4, 2014.

D. C. Montgomery, C. L. Jennings and M. Kulahci, Introduction to Time Series Analysis and Forecasting Second Edition, John Wiley & Sons, Inc, 2015.

G. Nason, "Stationary and Non-Stationary Time Series," in Statistics in Volcanology, 2006.

S. Khan and H. Alghulaiakh, "ARIMA Model for Accurate Time Series Stocks Forecasting," International Journal of Advanced Computer Science and Applications (IJACSA), vol. 11, 2020.


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