JOURNAL ARTICLE

Stock Market Prediction using Feed-forward Artificial Neural Network

Suraiya Jabin

Year: 2014 Journal:   International Journal of Computer Applications Vol: 99 (9)Pages: 4-8

Abstract

This paper presents computational approach for stock market prediction.Artificial Neural Network (ANN) forms a useful tool in predicting price movement of a particular stock.In the short term, the pricing relationship between the elements of a sector holds firmly.An ANN can learn this pricing relationship to high degree of accuracy and be deployed to generate profits with sufficiently large amounts of data, preferably in times of low volatility and over a short time period.Experimental results are presented to demonstrate the performance of the proposed system.The paper also aims to suggest about training algorithms and training parameters that must be chosen in order to fit time series kind of complicated data to a neural network model.The proposed model succeeded in prediction of the trends of stock market with 100% prediction accuracy.

Keywords:
Computer science Stock market prediction Artificial neural network Stock market Artificial intelligence Stock (firearms) Machine learning

Metrics

37
Cited By
3.01
FWCI (Field Weighted Citation Impact)
8
Refs
0.93
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Stock Market Forecasting Methods
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Financial Distress and Bankruptcy Prediction
Social Sciences →  Business, Management and Accounting →  Accounting
Imbalanced Data Classification Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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