A stock selection DSS combining AI and technical analysis

Seng-cho Chou, Hsien-jung Hsu, Chau-chen Yang and Feipei Lai

Annals of Operations Research, 1997, vol. 75, issue 0, 335-353

Abstract: Both technical analysis and artificial intelligence are popular and promising approaches for the construction of intelligent financial application systems, but any particular method alone might not be sufficient. Instead of pursuing the construction of a perfect system using any one particular technique, this paper focuses on the study of the Intelligent Stock Selection Decision Support System (ISSDSS) that adopts both traditional technical analysis and artificial intelligence in dealing with the stock selection problem. ISSDSS analyzes the Taiwan stock market using various technical analysis techniques including technical indicators, charts analysis, Japanese candlesticks philosophy, and Dow theory, giving the basis for the evaluation of the price and trend of stocks, trading signals, and trading prices. AI techniques built upon fuzzy decision rules are employed to double-check the results from technical analysis. The performance of ISSDSS was evaluated by simulating the stock selection in the Taiwan stock market from January 1990 to April 1995. The result confirms that the synergy of technical analysis and artificial intelligence outperforms systems using any one particular technique alone. Copyright Kluwer Academic Publishers 1997

Date: 1997
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DOI: 10.1023/A:1018923916424

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