A GA-Artificial Neural Network Hybrid System for Financial Time Series Forecasting

被引：0
|
作者：
Nair, Binoy B. [1 ]
Sai, S. Gnana [1 ]
Naveen, A. N. [1 ]
Lakshmi, A. [1 ]
Venkatesh, G. S. [1 ]
Mohandas, V. P. [1 ]
机构：
[1] Amrita Vishwa Vidyapeetham, Coimbatore 641105, Tamil Nadu, India
来源：
INFORMATION TECHNOLOGY AND MOBILE COMMUNICATION | 2011年 / 147卷
关键词：
Genetic algorithm; artificial neural networks; financial; time series; STOCK-MARKET; ACCURACY;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Accurate prediction of financial time series, such as those generated by stock markets, is a highly challenging task due to the highly nonlinear nature of such series. A novel method of predicting the next day's closing value of a stock market is proposed and empirically validated in the present study. The system uses an adaptive artificial neural network based system to predict the next day's closing value of a stock market index. The proposed system adapts itself to the changing market dynamics with the help of genetic algorithm which tunes the parameters of the neural network at the end of each trading session so that best possible accuracy is obtained. The effectiveness of the proposed system is established by testing on five international stock indices using ten different performance measures.
引用
收藏
页码：499 / 506
页数：8
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