Abstract
Developing robust trading rules for forex trading remains a significant challenge for both academics and practitioners. We employ a genetic algorithm to evolve a diverse set of profitable trading rules based on weighted moving average method. We use the daily closing rates between four pairs of currencies – EUR/USD, GBP/USD, USD/JPY, USD/CHF – to develop and evaluate our method. Results are presented for all four currency pairs over the 16 years from 2000 to 2015. Developed approach yields acceptably high returns on out-of-sample data. The rules obtained using our genetic algorithm result in significantly higher returns than those produced by rules identified through exhaustive search.
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Galeshchuk, S., Mukherjee, S. (2018). FOREX Trading Strategy Optimization. In: Bucciarelli, E., Chen, SH., Corchado, J. (eds) Decision Economics: In the Tradition of Herbert A. Simon's Heritage. DCAI 2017. Advances in Intelligent Systems and Computing, vol 618. Springer, Cham. https://doi.org/10.1007/978-3-319-60882-2_9
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DOI: https://doi.org/10.1007/978-3-319-60882-2_9
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