Application of adaptive RPCL-CLP with trading system to foreign exchange investment

Author

Cheung, Yiu-Ming ; Lai, Helen Z H ; Xu, Lei

Author_Institution

Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong

Volume

1

fYear

1996

fDate

3-6 Jun 1996

Firstpage

131

Abstract

In this paper, an adaptive rival penalized competitive learning and combined linear prediction model is applied to the forecast of stock price and exchange rate. As shown by the experimental results, this approach not only is better than Elman net and MA(q) models in the criterion of root mean square error, but also can bring in more returns in the trade between US dollar and German Deutschmark with the association of a trading system. Moreover, whatever trading strategies with different risks are used in the trading system, adaptive RPCL-CLP can always keep the profits increasing as time goes through

Keywords

forecasting theory; foreign exchange trading; unsupervised learning; adaptive RPCL-CLP; adaptive rival penalized competitive learning; combined linear prediction model; exchange rate forecasting; foreign exchange investment; root mean square error criterion; stock price forecasting; trading system; Adaptive systems; Application software; Buffer storage; Computer science; Exchange rates; Investments; Predictive models; Root mean square; Terminology; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1996., IEEE International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-7803-3210-5

Type

conf

DOI

10.1109/ICNN.1996.548879

Filename

548879