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

Farnaz Ghashami · Kamyar Kamyar · S. Ali Riazi

27 citations0/0 files storedApplied Economics and Finance

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Stock Market Forecasting Methods Neural Networks and Applications Forecasting Techniques and Applications

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.

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2003Financial time series forecasting using support vector machines 2016Stock market index prediction using artificial neural network 2016Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model 2020Stock Market Forecasting Using Computational Intelligence: A Survey 2018HYBRID FUZZY NEURAL NETWORK TO PREDICT PRICE DIRECTION IN THE GERMAN DAX-30 INDEX 2020Optimizing LSTM Based Network For Forecasting Stock Market 2008Prediction of S&P 500 and DJIA stock indices using Particle Swarm Optimization technique

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