Robustness Test of Genetic Algorithm on Generating Rules for Currency Trading

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@Article{DENG:2012:PCS,

• author = "Shangkun Deng and Yizhou Sun and Akito Sakurai",
• title = "Robustness Test of Genetic Algorithm on Generating Rules for Currency Trading",
• journal = "Procedia Computer Science",
• volume = "13",
• pages = "86--98",
• year = "2012",
• note = "Proceedings of the International Neural Network Society Winter Conference (INNS-WC2012)",
• keywords = "genetic algorithms, genetic programming, Optimisation algorithm, Foreign exchange, Robustness test, Technical analysis, Financial prediction",
• ISSN = "1877-0509",
• DOI = "doi:10.1016/j.procs.2012.09.117",
• URL = "http://www.sciencedirect.com/science/article/pii/S1877050912007247",
• abstract = "In trading in currency markets, reducing te mean of absolute or squared errors of predicted values is not valuable unless it results in profits. A trading rule is a set of conditions that describe when to buy or sell a currency or to close a position, which can be used for automated trading. To optimise the rule to obtain a profit in the future, a probabilistic method such as a genetic algorithm (GA) or genetic programming (GP) is used, since the profit is a discrete and multimodal function with many parameters. Although the rules optimised by GA/GP reportedly obtain a profit in out-of-sample testing periods, it is hard to believe that they yield a profit in distant out-of-sample periods. In this paper, we first consider a framework where we optimise the parameters of the trading rule in an in-sample training period, and then execute trades according to the rule in its succeeding out-of-sample period. We experimentally show that the framework very often results in a profit. We then consider a framework in which we conduct optimization as above and then execute trades in distant out-of-sample periods. We empirically show that the results depend on the similarity of the trends in the training and testing periods.",

}

Genetic Programming entries for Shangkun Deng Yizhou Sun Akito Sakurai

Citations