Non-linear,hybrid exchange rate modeling and trading profitability in the foreign exchange market |
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| Institution: | 1. Department of Finance, HEC Paris, 1 rue de la Libération, 78351 Jouy en Josas, France;2. Sauder School of Business, University of British Columbia, 2053 Main Mall, Vancouver, BC, Canada V6T1Z2;3. University of Zürich and Swiss Finance Institute (SFI), Department of Banking and Finance, Plattenstrasse 14, 8032 Zürich, Switzerland;1. Department of Anatomy, University of Otago, Dunedin, New Zealand;2. Department of Anatomy, Anhui Medical University, Hefei, China;1. Sasol, Sasolburg, South Africa;2. Department of Electrical, Electronic, and Computer Engineering, University of Pretoria, Pretoria, South Africa;1. Midwest Engineering Associates, Inc., Peoria, IL, United States;2. Parks College of Engineering, Aviation and Technology, Saint Louis University, St. Louis, MO, United States |
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| Abstract: | A neuro-fuzzy decision-making technology is designed and implemented to obtain the optimal daily currency trading rule. It is found that a non-linear, artificial neural network exchange rate microstructure (hybrid) model combined with a fuzzy logic controller generates a set of trading strategies that earn a higher rate of return compared to the simple buy-and-hold strategy. After accounting for realistic transaction costs, the gains from utilizing a dynamic, neuro-fuzzy model are still present. |
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