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.
Dr. Binoy B. Nair, Xavier, N., Mohandas, V. P., Sathyapal, A., Anusree, E. G., Kumar, P., and Ravikumar, V., “A GA-optimized SAX-ANN based Stock Level Prediction System”, International Journal of Computer Applications, vol. 106, 2014.