Work

Application of the Arima Model for Stock Price Prediction of PT Adaro Energy Tbk: A Time Series Analysis during the Energy Transition Period

Year: 2024

Type: article

Abstract: This study examines the stock price movements of PT Adaro Energy Tbk (ADRO) using the Autoregressive Integrated Moving Average (ARIMA) model, with a particular focus on the energy transition period. Employing daily closing price data from December 27, 2023, to December 24, 2024, this research utilizes a quantitative time series approach to develop a robust predictive model. The analysis results indicate that the ARIMA (2,1,0) model demonstrates the best performance based on the Sum of Squared Errors (SSE), Akaike Information Criterion (AIC), and Schwarz Information Criterion (SIC). This model effectively captures stock price movement patterns, including significant volatility observed during the business unit spin-off period. The forecast for the next 20 periods suggests a stable trend with a satisfactory level of accuracy. These findings offer valuable insights for investors and analysts in understanding the stock price dynamics of energy companies undergoing business transformations.

Source: Symmetry & Sigma Journal of Mathematical Structures and Statistical Patterns

DOI: 10.58989/symmerge.v1i2.23

Authors: Faiz Zamzami, Azzahra Ramadhani, Azizah Nurul Putri, Wahyuni Windasari

Institution: Universitas Putra Bangsa

Language: English

Topic: Stock Market Forecasting Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

OpenAlex ID: W4407269913

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