FORECASTING THE STOCK PRICE OF COAL AND COAL COMMODITY COMPANIES USING THE ARIMA AND ARCH/GARCH MODELS FOR 2011-2022 - Nuryadin, Didi; Sarayuda, Ida Bagus Putu Cesario Putra; Nada, Dewi Qutrun; Ira (Journal of Indonesian Applied Economics, 2024)
Purpose This research is a case study for the reference price of coal and coal export companies. Coal firms are one of Indonesia's main sectors within the mining industry. Design/methodology/approach In this study, ARIMA and ARCH/GARCH methods were developed to predict the share price of coal companies in Indonesia. Using ARIMA and ARCH models, it can predict accurately and quite well based on MAPE values between 6 – 20%. In addition, the movement of projections between the benchmark price and the stock price is directly proportional. Findings The study highlighted the significant influence of geopolitical events, such as the Russia-Ukraine war, and post-pandemic economic conditions on the coal industry. These factors were found to affect the stock prices of coal companies, making the forecasting models particularly valuable for adjusting to market changes. The findings provide valuable insights for investors in the coal sector, indicating that advanced econometric models can be used to make informed investment decisions. By understanding the impact of external events and identifying the most accurate forecasting models, investors can potentially enhance their investment strategies in the volatile coal market. Research limitations/implications The research limitation/implication as described in the document is centered on the scope of the study and its implications. Specifically, the research is a case study focusing on the reference price of coal and coal export companies, particularly within Indonesia's mining sector. This narrow focus means the findings may not be directly applicable to other sectors or geographical regions without further study. Additionally, the reliance on ARIMA and ARCH/GARCH methods for predicting stock prices, while effective within the parameters of this study, suggests a limitation in the methodology that may not account for all variables influencing stock prices, such as unforeseen geopolitical events or sudden market shifts. The implication here is that while the study provides valuable insights into the coal sector and offers a methodological approach for forecasting, its applicability is limited by its specific focus and the inherent unpredictability of the stock market. Originality/value This study is essential due to the post-pandemic covid 19 and the Russia - Ukraine conflict, influencing this country’s high local coal demand. The phenomenon brings a new paradigm to investors for investing in coal companies. Investors need a media to hustle with stock price growth to seek profit.