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| Author: | Dunis, C.L. Laws, J. Sermpinis, G. |
| Title: | Modelling and trading the EUR/USD exchange rate at the ECB fixing |
| Journal: | European Journal of Finance
2010 : JUL-SEP, VOL. 16:5-6, p. 541-560 |
| Index terms: | neural networks perception trading quantitative techniques euro dollars exchange rates European central bank |
| Freeterms: | confirmation filters higher-order neural networks Psi Sigma networks recurrent neural networks leverage multi-layer perception networks quantitative trading strategies |
| Language: | eng |
| Abstract: | Based on the European Central Bank (ECB) fixing series with only auto-regressive terms as inputs and by benchmarking four different NN designs representing a higher-order neural network (HONN), a Psi Sigma Network and a recurrent neural network with the classic multilayer perception (MLP) and some traditional techniques. The article uses the EUR/USD daily fixing by the ECB as many financial institutions are ready to trade at this level and it is therefore possible to leave orders with a bank for business to be transacted on that basis and suggests the MLP does remarkably well and outperforms all other models in a simple trading simulation exercise. However, when more sophisticated trading strategies using confirmation filters and leverage are applied, the HONN network produces better results and outperforms all other NN and traditional statistical models in terms of annualized return. |
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