Stock market index prediction using artificial neural network

Authors

  • Amin Hedayati Moghaddam Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran
  • Moein Hedayati Moghaddam Faculty of Managing and Accounting, College of Farabi, University of Tehran, Qom, Iran
  • Morteza Esfandyari Department of Chemical Engineering, Faculty of Engineering, University of Bojnord, ,Bojnord, Iran

Keywords:

NASDAQ, ANN, Prediction

Abstract

In this study the ability of artificial neural network (ANN)in forecasting the daily NASDAQ stock exchange rate was investigated. Several feed forward ANNs that were trained by the back propagation algorithm have been assessed. The methodology used in this study considered the short-term historical stock prices as well as the day of week as inputs. Daily stock exchange rates of NASDAQ from January 28, 2015 to 18 June, 2015 are used to develop a robust model. First 70 days (January 28 to March 7) are selected as training dataset and the last 29 days are used for testing the model prediction ability. Networks for NASDAQ index prediction for two type of input dataset (four prior days and nine prior days) were developed and validated.

Doi:  https://doi.org/10.1016/j.jefas.2016.07.​002

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Published

2016-12-01

How to Cite

Hedayati Moghaddam, A. ., Hedayati Moghaddam, M. ., & Esfandyari, M. . (2016). Stock market index prediction using artificial neural network. Journal of Economics, Finance and Administrative Science, 21(41), 89–93. Retrieved from https://revistas.esan.edu.pe/index.php/jefas/article/view/142

Issue

Vol. 21 No. 41 (2016): July - December

Section

Artículos

License

Copyright (c) 2016 Journal of Economics, Finance and Administrative Science

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.