Short term stock selection with case-based reasoning technique |
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| Affiliation: | 1. Toyota Central R&D Labs., Inc., Nagakute, Aichi 480-1192, Japan;2. Research Center for Integrated Quantum Electronics, Hokkaido University, Sapporo, Hokkaido 060-8628, Japan;3. Green Mobility Collaborative Research Center, Nagoya University, Nagoya, Aichi 464-8603, Japan;1. KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure links 653, B-9000 Gent, Belgium;2. Laboratory of Hydrology and Water Management, Ghent University, Coupure links 653, B-9000 Gent, Belgium |
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| Abstract: | Stock selection is an important decision making problem. Trading strategies and rules based on fundamental and technical analysis can be used for decision making process. In this paper, we propose an intelligent stock selection method, which is called case-based reasoning (CBR). This technique uses the fundamental and technical indicators to identify the winning stocks around the earning announcements. CBR method is compared with other artificial intelligence techniques such as multi layer perceptron (MLP), decision trees (QUEST, Classification and Regression Trees, C5), generalized rule induction (GRI) and logistic regression. We show that the performance of CBR is better than the performance of other techniques in terms of classification accuracy, average return, Sharpe ratio and ideal profit. |
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| Keywords: | Stock selection Case-based reasoning Intelligent system Computational intelligence Genetic algorithms Earning analysis |
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