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74. Progress Report: Improving the Stock Price Forecasting Performance of the Bull Flag Heuristic with Genetic Algorithms and Neural Networks

William Leigh4, Edwin Odisho4, Noemi Paz4 and Mario Paz5

(4)  Department of MIS, University of Central Florida, Orlando, FL
(5)  Department of Civil Engineering, University of Louisville, Louisville, Kentucky
Abstract
We back-test a pattern-based heuristic from stock market technical analysis on price and volume time series data for Alcoa Aluminum Company’s common stock. Promising results are obtained using a pattern matching approach implemented with spreadsheet technology. Improvement in these results are attained through the application of neural networks and genetic algorithms. Results are confirmed statistically.

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