Title :
Predicting the Canadian spot exchange rate with neural networks
Author :
Staley, Mark ; Kim, Peter
Author_Institution :
Dept. of Phys., Guelph Univ., Ont., Canada
Abstract :
Reports on the feasibility of applying neural networks to the problem of forecasting the Canada/US spot exchange rate. The inputs to the network consist of the short-term trend in the spot rate (Monday-Thursday) and the change in interest rate spread between the two countries (Wednesday-Thursday). The output is a prediction of the exchange rate on Friday. The model is able to explain 6.6% of the variance in the data between November 1991 and June 1993 (out of the sample), yielding a success rate of 59% on directional forecasts
Keywords :
electronic trading; financial data processing; forecasting theory; foreign exchange trading; neural nets; Canada/US spot exchange rate prediction; currency exchange; directional forecasts; interest rate spread; neural networks; sample; short-term trend; success rate; variance; Economic indicators; Electronic mail; Exchange rates; Mathematics; Monitoring; Neural networks; Physics; Predictive models; Statistics; Testing;
Conference_Titel :
Computational Intelligence for Financial Engineering, 1995.,Proceedings of the IEEE/IAFE 1995
Conference_Location :
New York, NY
Print_ISBN :
0-7803-2145-6
DOI :
10.1109/CIFER.1995.495261
