Acta Univ. Agric. Silvic. Mendelianae Brun. 2005, 53, 109-116
Published online 2014-12-27

Selected aspects of modelling of foreign exchange rates with neural networks

Václav Mastný

Ústav financí, Mendelova zemědělská a lesnická univerzita v Brně, Zemědělská 1, 613 00 Brno, Česká republika

This paper deals with forecasting of the high-frequency foreign exchange market with neural networks. The objective is to investigate some aspects of modelling with neural networks (impact of topology, size of training set and time horizon of the forecast on the performance of the network). The data used for the purpose of this paper contain 15-minute time series of US dollar against other major currencies, Japanese Yen, British Pound and Euro. The results show, that performance of the network in terms of correct directorial change is negatively influenced by increasing number of hidden neurons and decreasing size of training set. The performance of the network is influenced by sampling frequency.


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