Using learning classifier system for making investment strategies based on institutional analysis

Ju Yin Lin, Chi Pin Cheng, Wen Chih Tsai, An-Pin Chen

研究成果: Conference contribution同行評審

3 引文 斯高帕斯(Scopus)

摘要

The artificial intelligence can dynamically learn and adapt to the change of environments for maximizing the desired goals. This paper conducts simulation experiment to evolve learning classifier system (LCS) for short-term stock forecast decision. Since stock price trend is influenced by unknown and unpredictable surroundings, using LCS to model the fluctuations on financial market allows for the capability to discover the patterns of future trends. Furthermore, the institutional investment is the main consideration of this research by implementing LCS for making strategies. More specifically, LCS is capable of evolving from generation to generation, and in this way can provide the highest profit for future decision-making. In simulation work using real financial data, it is found that LCS produces great profits, and is quite practical for investors.

原文English
主出版物標題Proceedings of the IASTED International Conference on Artificial Intelligence and Applications (as part of the 22nd IASTED International Multi-Conference on Applied Informatics)
編輯M.H. Hamza
頁面765-769
頁數5
出版狀態Published - 1 十二月 2004
事件Proceedings of the IASTED International Conference on Artificial Intelligence and Applications (as part of the 22nd IASTED International Multi-Conference on Applied Informatics - Innsbruck, Austria
持續時間: 16 二月 200418 二月 2004

出版系列

名字Proceedings of the IASTED International Conference. Applied Informatics

Conference

ConferenceProceedings of the IASTED International Conference on Artificial Intelligence and Applications (as part of the 22nd IASTED International Multi-Conference on Applied Informatics
國家Austria
城市Innsbruck
期間16/02/0418/02/04

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