Cash Flow Forecasting for Companies Listed on the Indonesia Stock Exchange Using the ARIMA Model
Abstract
Cash flow forecasting plays a crucial role in supporting financial stability and strategic decision-making for businesses. This study aims to analyze and forecast the operating cash flow of healthcare sector companies listed on the Indonesia Stock Exchange (IDX) using the ARIMA (Autoregressive Integrated Moving Average) model. The dataset consists of quarterly operating cash flows from 17 companies over the period 2020–2024. This research uses a quantitative approach with time series analysis. The modeling process includes stationarity testing, parameter identification, model training, and evaluation using MAPE, MAE, RMSE, and R-squared as performance metrics. The results indicate that all cash flow data are stationary, and the ARIMA models provide strong predictive performance, with MAPE values below 20% and R-squared consistently above 0.90. These findings suggest that the healthcare sector exhibits stable cash flow patterns and resilience to short-term fluctuations. The study concludes that ARIMA is an effective tool for short-term financial forecasting in the healthcare industry. The implications of this study suggest that the forecasting results can be used as a reliable basis for budget planning, liquidity management, and investment decision-making in healthcare companies.
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References
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