- author = "Badarch Tserenchimed and Shu Liu and Hitoshi Iba",
- title = "A trading method in {FX} using evolutionary algorithms: extensions based on reverse trend and settlement timing",
- booktitle = "GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation",
- year = "2011",
- editor = "Natalio Krasnogor and Pier Luca Lanzi and Andries Engelbrecht and David Pelta and Carlos Gershenson and Giovanni Squillero and Alex Freitas and Marylyn Ritchie and Mike Preuss and Christian Gagne and Yew Soon Ong and Guenther Raidl and Marcus Gallager and Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and Nikolaus Hansen and Silja Meyer-Nieberg and Jim Smith and Gus Eiben and Ester Bernado-Mansilla and Will Browne and Lee Spector and Tina Yu and Jeff Clune and Greg Hornby and Man-Leung Wong and Pierre Collet and Steve Gustafson and Jean-Paul Watson and Moshe Sipper and Simon Poulding and Gabriela Ochoa and Marc Schoenauer and Carsten Witt and Anne Auger",
- isbn13 = "978-1-4503-0690-4",
- keywords = "genetic algorithms, genetic programming: Poster",
- pages = "139--140",
- month = "12-16 " # jul,
- organisation = "SIGEVO",
- address = "Dublin, Ireland",
-
DOI = "
doi:10.1145/2001858.2001937",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- abstract = "In foreign exchange (FX) markets, the key issues to achieve profitable trading rules are the combination of the indicators, selection of their parameters, and decision of the trade timing for orders and settlements. In this paper, we present a trading system using a combination of genetic algorithm (GA) and genetic programming (GP). Unlike related researches on this problem, our work focuses on two aspects. First, a calculation of appropriate settlement timing is proposed, to make more profits and less losses. Second, reverse trend data are generated using in-sample data, to overcome the over fitting problem and suppress the risk of loss. To examine the effectiveness of the method, we employed simulations using real-world trading intraday data. It is verified the enhanced capability of our method to make consistent gain out-of-sample and avoid large draw-downs.",
-
notes = "Also known as \cite{2001937} Distributed on CD-ROM at
GECCO-2011.
ACM Order Number 910112.",
