DocumentCode
3258711
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
Volume
2
fYear
1995
fDate
Nov/Dec 1995
Firstpage
1018
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.487560
Filename
487560
Link To Document