Application of artificial neural network models and principal component analysis method in predicting stock prices on Tehran Stock Exchange

被引：67

作者：

Zahedi, Javad ^{[1
]}

Rounaghi, Mohammad Mahdi ^{[1
]}

机构：

[1] Islamic Azad Univ, Mashhad Branch, Dept Accounting, Mashhad, Iran

来源：

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2015年 / 438卷

关键词：

Artificial neural networks; Prediction stock price; Principal component analysis;

D O I：

10.1016/j.physa.2015.06.033

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

Stock price changes are receiving the increasing attention of investors, especially those who have long-term aims. The present study intends to assess the predictability of prices on Tehran Stock Exchange through the application of artificial neural network models and principal component analysis method and using 20 accounting variables. Finally, goodness of fit for principal component analysis has been determined through real values, and the effective factors in Tehran Stock Exchange prices have been accurately predicted and modeled in the form of a new pattern consisting of all variables. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：178 / 187

页数：10

共 24 条

[1]

Azizian A., 2006, THESIS

[2]

Bordman A.E., 2000, APPL EC

[3]

Botshekan M., 2000, THESIS

[4]

Dayhoff J.E., 1990, NEURAL NETWORK PRINC

[5]

Dimitris Koulouriotis, 2002, FUZZY EC REV, P23

[6] Cross-correlation and the predictability of financial return series [J].

Duan, Wen-Qi ;

Stanley, H. Eugene .

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2011, 390 (02) :290-296

[7]

Egeli B., 2003, Stock Market Prediction Using Artificial Neural Networks

[8]

Javadian A., 2006, THESIS

[9]

Keshmiri M., 2010, THESIS

[10]

Khalouzadeh H., 1998, J EC MODEL RES, V69, P1

← 1 2 3 →