Work

Accuracy Driven Artificial Neural Networks in Stock Market Prediction

Year: 2012

Type: article

Abstract: Globalization has made the stock market prediction (SMP) accuracy more challenging and rewarding for the researchers and other participants in the stock market.Local and global economic situations along with the company's financial strength and prospects have to be taken into account to improve the prediction accuracy.Artificial Neural Networks (ANN) has been identified to be one of the dominant data mining techniques in stock market prediction area.In this paper, we survey different ANN models that have been experimented in SMP with the special enhancement techniques used with them to improve the accuracy.Also, we explore the possible research strategies in this accuracy driven ANN models.

Source: International Journal on Soft Computing

DOI: 10.5121/ijsc.2012.3203

Author: Selvan Simon

Institution: Shreemati Nathibai Damodar Thackersey Women's University

Language: English

Topic: Stock Market Forecasting Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: bronze

OpenAlex ID: W2334767398

FWCI: 2.121

Cites: 26

Cited by: 40

Related to: 10