Agent-based evolutionary optimisation of trading strategies. (21st February 2008)

• Record Type: Journal Article
• Authors: Ni, Jiarui; Luo, Dan; Ou, Yuming; Luo, Chao
• Is Part Of: International journal of intelligent information and database systems. Volume 2:Number 1(2008)
• Page Start: 25
• Page End: 48
• Publication Date: 2008-02-21
• Subjects: genetic algorithms -- GAs -- optimisation -- agents -- multi-agent systems -- MAS -- agent-based systems -- trading strategies -- data mining -- stock data; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

The backtesting and optimisation of trading strategies has emerged as an interesting research and experimental problem in both finance and Information Technology (IT) fields. However, it is a non-trivial task to effectively and efficiently optimise trading strategies, not to mention the optimisation in the real-world situations. This paper discusses the application of evolutionary technologies (genetic algorithm in particular) to the optimisation of trading strategies. Experimental results show that this approach is promising. Due to the complexity involved in the optimisation process, we further present an agent-based system that can help users easily specify and execute optimisation jobs to their advantages.