A GA-optimized SAX- ANN based Stock Level Prediction System

Forecasting stock price movements is of immense importance to any stock trader. However, traditionally, this has been accomplished using technical analysis tools. In this study, an attempt has been made to employ data mining to identify the one-day-ahead stock price levels. Two different approaches...

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Bibliographic Details
Published in:International journal of computer applications 2014-01, Vol.106 (15)
Main Authors: Nair, Binoy B, Xavier, Nikhil, Mohandas, V P, Sathyapal, Adarsh, G, Anusree E, Kumar, Pawan, Ravikumar, Vignesh
Format: Article
Language:English
Subjects:
Data mining
Empirical analysis
Forecasting
Learning theory
Markets
Movements
Neural networks
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Summary:Forecasting stock price movements is of immense importance to any stock trader. However, traditionally, this has been accomplished using technical analysis tools. In this study, an attempt has been made to employ data mining to identify the one-day-ahead stock price levels. Two different approaches are considered. The two approaches are empirically validated on twelve stock price datasets, with the stocks drawn from the Indian, US and UK stock markets. Results indicate that both the approaches proposed in the present study are capable of successfully forecasting the one-day-ahead stock price levels.
ISSN:0975-8887
0975-8887
DOI:10.5120/18594-9840