Predicting Future Cash Flows Using Autoregressive Integrated Moving Average (ARIMA) - Vika Fitranita; Rola Tri Rahayu; Eddy Suranta; Nikmah Nikmah; Halimatusyadiah Halimatusyadiah (UNIVED Press, 2024)
This study aims to provide empirical evidence of the ability of operating cash flows to predict future cash flows, ability of net income to predict future cash flows and proves that net income is better at predicting future cash flows compared to operating cash flows. This study was tested using autoregressive integrated moving average analysis. The samples used in this study are tourism, hotel, and restaurant companies listed on the Indonesian Stock Exchange in 2018-2022. The sample in this study was selected using purposive sampling method with a total sample of 418 observations. Before forecasting, the stationarity of the data is seen through ACF and PACF plots and unit root test. The results showed that the operating cash flow data did not meet the assumption of stationarity, so the first differencing process was carried out so that the data obtained was stationary so that the best operating cash flow model for predicting future cash flows was the ARIMA model (3,1,0) and for net income data, it had fulfilled the stationarity assumption, so it was not the differencing process is carried out so that the best model of net income is in forecasting ARIMA's future cash flows (3,0,0).