Approximating foreign exchange rates by recurrent neural network dynamics

被引：0
|
作者：
Li, LK [1 ]
机构：
[1] Hong Kong Polytech Univ, Dept Appl Math, Hong Kong, Hong Kong, Peoples R China
来源：
PROGRESS IN CONNECTIONIST-BASED INFORMATION SYSTEMS, VOLS 1 AND 2 | 1998年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ups and downs in financial markets are collective human decisions which are the result of the dynamics of neurons. In this paper, we show how to model these market behavior by recurrent neural networks. As a non-linear auto-regression model, the results show that the discrete-time recurrent neural net approximates the foreign exchange rates rather close.
引用
收藏
页码：1295 / 1298
页数：4
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