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

摘要

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.