• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2008, Vol. 30 ›› Issue (5): 150-153.

• 论文 • 上一篇    下一篇

基于神经网络LAMSTAR的短线股票预测研究

谢秀珍[1] 李建洋[2]   

  • 出版日期:2008-05-01 发布日期:2010-05-19

  • Online:2008-05-01 Published:2010-05-19

摘要:

股票预测在金融领域是一个重要的课题。LAMSTAR是一个用于存储、识别、比较和决策的网络系统。本文尝试开发一个关于短期股票预测的LAMSTAR网络应用程序,每一次预测都会从历史数据里获取股票特征,然后输入LAMSTAR网络。网络会自动检测各特征之间的多维非线性关系并编码,然后根据预测的趋势进行交易。本文提供了三个公司的预测结果,该预测结果非常有效。

关键词: 神经网络 LAMSTAR 股票预测 短期预测

Abstract:

Stock prediction is an important issue in finance. LAMSTAR is a system of networks for storage, recognition, comparison and decision. This paper attem pts to explore the LAMb'TAR network application in short-term stock market prediction. For each prediction, the stock features extracted from the histo  orical data are fed to the LAMSTAR network, in which the multi-dimensional non-linear connections between the features are detected and encoded in link weights. If the stock price is predicted to go up in the following trading day, LAMSTAR will send out a buy signal to initiate a transaction. Three expe rimental results with exciting returns of different companies are presented to validate the efficiency of this approach.

Key words: neural network, LAMSTAR, stock prediction;short term prediction