Enhance the performance of Neural Networks for Stock Market Prediction: An analytical study

被引：0

作者：

Boonpeng, Sabaithip ^{[1
]}

Jeatrakul, Piyasak ^{[1
]}

机构：

[1] Mae Fah Luang Univ, Sch Informat Technol, Muang, Chiang Rai, Thailand

来源：

2014 NINTH INTERNATIONAL CONFERENCE ON DIGITAL INFORMATION MANAGEMENT (ICDIM) | 2014年

关键词：

data mining; artificial neural network; prediction model; financial prediction;

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：

Stock market prediction is a challenging task in the machine learning research. The challenge is how to guide the investors when is the right time to buy or to sell. In the present day, there are numbers of machine learning techniques applied to predict the stock market such as Genetic Algorithm (GA), Support Vector Machines (SVM) and Artificial Neural Network (ANN). ANN is a major technique which is employed widely in this area. Therefore, in order to understand the trend of using ANN in the stock market prediction, the techniques to enhance the performance of ANN are reviewed. The period of the study is in the year between 2006 and 2013.

引用

页码：1 / 6

页数：6

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