Managerial Forecasting System Based on RBF Neural Network for Financial Data

Abstract

Forecasting systems are applied which are based on the latest statistical theory and artificial neural networks. The impact of these methods to risk reduction is judged in managerial decision-making. The fundamental question arises whether non-linear methods like neural networks can help modeling any non-linearities being inherent within the estimated statistical model. The proposed novel modeling approach is applied to high frequency time series of EUR/USD exchange rates (EUR currency against the US dollar. Our results show that the proposed neural approach achieves better forecast accuracy on the validation dataset than most available statistical techniques.