Work

Prediction of Stock Market Index Using a Hybrid Technique of Artificial Neural Networks and Particle Swarm Optimization

Year: 2021

Type: article

Abstract: In this paper we examine the ability of Artificial Neural Network methods (ANN) for predicting the stock market index. We first conduct an ANN analysis and then optimize the ANN model using Particle Swarm Optimization algorithm (PSO) to improve the prediction accuracy. In terms of data, we use NASDAQ index which is one of the most widely followed indices in the United States. Empirical results show that by determining the optimal set of biases and weights using PSO, we can augment the accuracy of the ANN model for this stock market data set.

Source: Applied Economics and Finance

DOI: 10.11114/aef.v8i3.5195

Authors: Farnaz Ghashami, Kamyar Kamyar, S. Ali Riazi

Institutions: Drexel University, The Ohio State University, Ruhr University Bochum

Language: English

Topic: Stock Market Forecasting Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W3155013200

FWCI: 3.043

Cites: 20

Cited by: 31

Related to: 10