Forecasting foreign exchange rates using recurrent neural networks

1996 ◽  
Vol 10 (6) ◽  
pp. 567-582 ◽  
Author(s):  
Paolo Tenti
Keyword(s):  
Neural Networks ◽  
Exchange Rates ◽  
Foreign Exchange ◽  
Recurrent Neural Networks ◽  
Foreign Exchange Rates

Forecasting Short-Term Exchange Rates

2011 ◽  
pp. 195-212
Author(s):  
Leong-Kwan Li ◽  
Wan-Kai Pang ◽  
Wing-Tong Yu ◽  
Marvin D. Troutt
Keyword(s):  
Neural Networks ◽  
Exchange Rates ◽  
Foreign Exchange ◽  
Recurrent Neural Networks ◽  
Foreign Exchange Rates ◽  
Short Term ◽  
Financial Strategy ◽  
Term Trend ◽  
Exchange Markets ◽  
Short Term Trend

Movements in foreign exchange rates are the results of collective human decisions, which are the results of the dynamics of their neurons. In this chapter, we demonstrate how to model these types of market behaviors by recurrent neural networks (RNN). The RNN approach can help us to forecast the short-term trend of foreign exchange rates. The application of forecasting techniques in the foreign exchange markets has become an important task in financial strategy. Our empirical results show that a discrete-time RNN performs better than the traditional methods in forecasting short-term foreign exchange rates.

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