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A stock selection DSS combining AI and technical analysis

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

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

Suggested Citation

  • Seng-cho Chou & Hsien-jung Hsu & Chau-chen Yang & Feipei Lai, 1997. "A stock selection DSS combining AI and technical analysis," Annals of Operations Research, Springer, vol. 75(0), pages 335-353, January.
    • Handle: RePEc:spr:annopr:v:75:y:1997:i:0:p:335-353:10.1023/a:1018923916424
    DOI: 10.1023/A:1018923916424
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    Cited by:

    1. Shivam Gupta & Sachin Modgil & Samadrita Bhattacharyya & Indranil Bose, 2022. "Artificial intelligence for decision support systems in the field of operations research: review and future scope of research," Annals of Operations Research, Springer, vol. 308(1), pages 215-274, January.
    2. Amita Sharma & Aparna Mehra, 2017. "Financial analysis based sectoral portfolio optimization under second order stochastic dominance," Annals of Operations Research, Springer, vol. 256(1), pages 171-197, September.
    3. Konstandinos Chourmouziadis & Dimitra K. Chourmouziadou & Prodromos D. Chatzoglou, 2021. "Embedding Four Medium-Term Technical Indicators to an Intelligent Stock Trading Fuzzy System for Predicting: A Portfolio Management Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1183-1216, April.

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