Forecasting the Stock Price of Coal and Coal Commodity Companies using the ARIMA and ARCH/GARCH Models for 2011-2022
Abstract
This study focuses on coal companies in Indonesia, a key sector in the mining industry. It explores how ARIMA and ARCH/GARCH models can predict the share prices of these companies. The results indicate that these models are effective, with Mean Absolute Percentage Error (MAPE) values ranging from 6 to 20 percent. The movement of stock prices is directly proportional to changes in the benchmark price. Additionally, it emphasizes the significant impact of geopolitical events, like the Russia-Ukraine conflict, and post-pandemic economic conditions on the coal industry. These factors have influenced coal company stock prices, highlighting the value of forecasting models in adapting to market fluctuations. The research provides important insights for investors, suggesting that advanced econometric models can help make informed investment decisions and enhance strategies in the volatile coal market by accounting for external events and model accuracy.
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