Stock market index prediction using artificial neural network

Amin Hedayati, Moein Hedayati () and Morteza Esfandyari
Additional contact information
Amin Hedayati: Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran
Moein Hedayati: 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

Journal of Economics, Finance and Administrative Science, 2016, vol. 21, issue 41, 89-93

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.

Keywords: NASDAQ; ANN; Predicción (search for similar items in EconPapers)
JEL-codes: C33 (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (36)

Downloads: (external link)
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3004032 Full text (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:joefas:0104

Access Statistics for this article

Journal of Economics, Finance and Administrative Science is currently edited by Nestor U. Salcedo

More articles in Journal of Economics, Finance and Administrative Science from Universidad ESAN 1652 Alonso de Molina, Santiago de Surco 15023, Lima, Peru. Contact information at EDIRC.
Bibliographic data for series maintained by ESAN Ediciones ().