Selected aspects of modelling of foreign exchange rates with neural networks
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...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Mendel University Press
2005-01-01
|
| Series: | Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis |
| Subjects: | |
| Online Access: | https://acta.mendelu.cz/53/3/0109/ |
| Summary: | 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. |
|---|---|
| ISSN: | 1211-8516 2464-8310 |