Abstract
Abstract Cash flow is one of the most important concepts of financial analysis at the moment. Cash flow forecasting is a key factor in the financial planning of large commercial banks. This paper describes methods of forecasting cash flow volumes using regression model, ARIMA model and MLP neural network model. As the practice has shown the use of classical models (regression and ARIMA) is preferable in the regions that are not subject to sharp economic changes, and MLP has shown greater efficiency in forecasting in large cities and regional centres, i.e. in places with greater economic activity, where the cash flow is affected by a greater number of factors.
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