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Book Chapter
Progress Report: Improving the Stock Price Forecasting Performance of the Bull Flag Heuristic with Genetic Algorithms and Neural Networks
Book Series
Lecture Notes in Computer Science
Publisher
Springer Berlin / Heidelberg
ISSN
0302-9743 (Print) 1611-3349 (Online)
Volume
Volume 1821/2000
Book
Intelligent Problem Solving. Methodologies and Approaches
DOI
10.1007/3-540-45049-1
Copyright
2000
ISBN
978-3-540-67689-8
DOI
10.1007/3-540-45049-1_74
Pages
17-28
Subject Collection
Computer Science
SpringerLink Date
Saturday, January 01, 2000
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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 Leigh
4
, Edwin Odisho
4
, Noemi Paz
4
and Mario Paz
5
(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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