A hybrid automated trading system based on multi-objective grammatical evolution

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@Article{journals/jifs/ContrerasHN17,

• author = "Ivan Contreras and Jose Ignacio Hidalgo and Laura Nunez-Letamendia",
• title = "A hybrid automated trading system based on multi-objective grammatical evolution",
• journal = "Journal of Intelligent and Fuzzy Systems",
• year = "2017",
• volume = "32",
• number = "3",
• pages = "2461--2475",
• keywords = "genetic algorithms, genetic programming, grammatical evolution",
• bibdate = "2017-05-28",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/jifs/jifs32.html#ContrerasHN17",
• DOI = "doi:10.3233/JIFS-16435",
• abstract = "This paper describes a hybrid automated trading system (ATS) based on grammatical evolution and microeconomic analysis. The proposed system takes advantage from the flexibility of grammars for introducing and testing novel characteristics. The ATS introduces the self-generation of new technical indicators and multi-strategies for stopping unforeseen losses. Additionally, this work copes with a novel optimization method combining multi-objective optimization with a grammatical evolution methodology. We implemented the ATS testing three different fitness functions under three mono-objective approaches and also two multi-objective ATSs. Experimental results test and compare them to the Buy and Hold strategy and a previous approach, beating both in returns and in number of positive operations. In particular, the multi-objective approach demonstrated returns up to 20percent in very volatile periods, proving that the combination of fitness functions is beneficial for the ATS.",

}

Genetic Programming entries for Ivan Contreras Jose Ignacio Hidalgo Perez Laura Nunez-Letamendia

Citations