Title :
Multivariate FOREX forecasting using artificial neural networks
Author :
Gan, Woon-Seng ; Ng, Kah-Hwa
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Abstract :
This paper investigates the use of artificial neural networks (ANN) to forecast the foreign exchange (FOREX) rates of major currencies, the Swiss Franc (CHF), Deutschemark (DEM) and Japanese Yen (JPY) against US dollars. Two ANN models using univariate and multivariate time series are examined here and benchmark against the random walk model. This paper extends the authors´ work (1995) by looking into the forecasting capability of the ANN models to handle the FOREX return series
Keywords :
financial data processing; forecasting theory; foreign exchange trading; neural nets; Deutschemark; FOREX return series; Japanese Yen; Swiss Franc; US dollars; currencies; foreign exchange rates; multivariate FOREX forecasting; neural networks; random walk model; time series; Artificial neural networks; Consumer electronics; Economic forecasting; Exchange rates; Load forecasting; Neural networks; Notice of Violation; Predictive models; Technology forecasting; Testing;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.487560
