RBF Network-Based Chaotic Time Series Prediction and It's Application in Foreign Exchange Market

DOI

10.2991/iske.2007.5How to use a DOI?

Keywords

Chaotic time series, Prediction, Phase space reconstruction, RBF network, Foreign exchange market

Abstract

The foreign exchange market is a chaotic dynamic system. We apply the RBF network-based chaotic time series prediction on the daily USD/RMB exchange rate. We apply the RBF network and phase space reconstruction to find the optimal embedding dimension in the foreign exchange market from the point view of forecasting. We find that the optimal embedding dimension is 10. As a result the dimension of the attractor of the market is about in the interval between 4 and 5. Finally, we use the optimal embedding dimension to implement the prediction.

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Li-li Ma
AU  - Xu-song Xu
PY  - 2007/10
DA  - 2007/10
TI  - RBF Network-Based Chaotic Time Series Prediction and It's Application in Foreign Exchange Market
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 19
EP  - 22
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.5
DO  - 10.2991/iske.2007.5
ID  - Ma2007/10
ER  -