The Application of Structured Feedforward Neural Networks to the Modelling of the Daily Series of Currency in Circulation

Abstract

One of the most significant factors influencing the liquidity of financial markets is the amount of currency in circulation. Even the central bank is responsible for the distribution of the currency it could not assess the demand for the currency as it is influenced by the non-banking sector. Therefore the amount of currency in circulation have to be forecasted. This paper introduces feedforward structured neural network model and discusses its applicability to the forecasting of the currency in circulation. The forecasting performance of the new neural network model is compared with an ARIMA model. The results indicates that the performance of the neural network model is slightly better and that both models might be applied at least as supportive tools for the liquidity forecasting.