An Investment Strategy for the Stock Exchange Using Neural Networks

被引：0

作者：

Wysocki, Antoni ^{[1
]}

Lawrynczuk, Maciej ^{[1
]}

机构：

[1] Warsaw Univ Technol, Inst Control & Computat Engn, PL-00665 Warsaw, Poland

来源：

2013 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS) | 2013年

关键词：

Stock exchange; prediction; nonlinear modeling; neural networks; soft computing;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes a neural system which helps to make the current investment decisions. Some well known financial indicators usually considered by investors are inputs of the system. The basic problem is to select appropriately the indicators which would give the best predictor. Two methods are used and compared: the combination method and the correlation method. To analyze the problem daily quotations of companies included in the Warsaw Stock Exchange Index (WIG20) are used.

引用

页码：183 / 190

页数：8

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