Neural Network Based Stock Market Forecasting

被引：0
|
作者：
El-Hammady, Ahmed Ismail [1 ]
Abo-Rizka, Mohamed [1 ]
机构：
[1] Arab Acad Sci Technol & Maritime Transport, Alexandria, Egypt
来源：
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2011年 / 11卷 / 08期
关键词：
Neural Network; Time Series; Forecast; ARIMA; Egypt Stock Market;
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：
We develop a useful prediction system in forecasting stock price for Egypt stock market (Egypt stock exchange weighted stock index, Commercial International Bank as CIB). The system is based on a recurrent neural network trained by using ARIMA analyses by differencing the raw data of the CIB series and then examining the ACF and PACF plots. The series can be identified as a nonlinear version of ARIMA (1, 1, 2). Neural networks trained by using first differentiation of data. The networks trained by using history data for 6-years ago to predict 12 weeks market trend.
引用
收藏
页码：204 / 207
页数：4
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