Prediction of high increases in stock prices using neural networks

被引：0

作者：

Michalak, K ^{[1
]}

Lipinski, P

机构：

[1] Wroclaw Tech Univ, PL-50370 Wroclaw, Poland

[2] Univ Strasbourg 1, CNRS, LSIIT, Strasbourg, France

[3] Univ Wroclaw, Inst Comp Sci, PL-51151 Wroclaw, Poland

来源：

NEURAL NETWORK WORLD | 2005年 / 15卷 / 04期

关键词：

neural networks; multi-layer perceptron; financial forecasting; stock market data prediction;

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：

This paper addresses the problem of stock market data prediction. It discusses the abilities of neural networks to learn and to forecast price quotations as well as proposes a neural approach to the future stock price prediction and detection of high increases or high decreases in stock prices. In order to validate the approach, a large number of experiments were performed on real-life data from the Warsaw Stock Exchange.

引用

页码：359 / 366

页数：8

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