Title
Ensemble learning of rule-based evolutionary algorithm using multi-layer perceptron for supporting decisions in stock trading problems
Abstract
Graphical abstractDisplay Omitted HighlightsRule pools for stock trading are generated by a rule-based evolutionary algorithm.Ensemble learning using MLP selects appropriate rule pools for trading decision.The proposed method shows better profitability than the other methods.The proposed method appropriately selects good rules depending on the situations. Classification is a major research field in pattern recognition and many methods have been proposed to enhance the generalization ability of classification. Ensemble learning is one of the methods which enhance the classification ability by creating several classifiers and making decisions by combining their classification results. On the other hand, when we consider stock trading problems, trends of the markets are very important to decide to buy and sell stocks. In this case, the combinations of trading rules that can adapt to various kinds of trends are effective to judge the good timing of buying and selling. Therefore, in this paper, to enhance the performance of the stock trading system, ensemble learning mechanism of rule-based evolutionary algorithm using multi-layer perceptron (MLP) is proposed, where several rule pools for stock trading are created by rule-based evolutionary algorithm, and effective rule pools are adaptively selected by MLP and the selected rule pools cooperatively make decisions of stock trading. In the simulations, it is clarified that the proposed method shows higher profits or lower losses than the method without ensemble learning and buy&hold.
Year
DOI
Venue
2015
10.1016/j.asoc.2015.07.020
Applied Soft Computing
Keywords
Field
DocType
Ensemble learning,Evolutionary computation,Rule-based algorithm,Multi-layer perceptron,Trend judgment,Stock trading
Trading strategy,Rule-based system,Evolutionary algorithm,Evolutionary computation,Multilayer perceptron,Profitability index,Artificial intelligence,Ensemble learning,Perceptron,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
36
C
1568-4946
Citations 
PageRank 
References 
8
0.49
16
Authors
3
Name
Order
Citations
PageRank
Shingo Mabu149377.00
Masanao Obayashi219826.10
Takashi Kuremoto319627.73