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Integrated Model of Multiple Kernel Learning and Differential Evolution for EURUSD Trading
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-03
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Currency trading is an important area for individual investors, government policy decisions, and organization investments.
In this study, we propose a hybrid approach referred to as MKL-DE, which combines multiple kernel learning (MKL) with differential evolution (DE) for trading a currency pair.
MKL is used to learn a model that predicts changes in the target currency pair, whereas DE is used to generate the buy and sell signals for the target currency pair based on the relative strength index (RSI), while it is also combined with MKL as a trading signal.
The new hybrid implementation is applied to EUR/USD trading, which is the most traded foreign exchange (FX) currency pair.
MKL is essential for utilizing information from multiple information sources and DE is essential for formulating a trading rule based on a mixture of discrete structures and continuous parameters.
Initially, the prediction model optimized by MKL predicts the returns based on a technical indicator called the moving average convergence and divergence.
Next, a combined trading signal is optimized by DE using the inputs from the prediction model and technical indicator RSI obtained from multiple timeframes.
The experimental results showed that trading using the prediction learned by MKL yielded consistent profits.
American Psychological Association (APA)
Deng, Shangkun& Sakurai, Akito. 2014. Integrated Model of Multiple Kernel Learning and Differential Evolution for EURUSD Trading. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1051581
Modern Language Association (MLA)
Deng, Shangkun& Sakurai, Akito. Integrated Model of Multiple Kernel Learning and Differential Evolution for EURUSD Trading. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1051581
American Medical Association (AMA)
Deng, Shangkun& Sakurai, Akito. Integrated Model of Multiple Kernel Learning and Differential Evolution for EURUSD Trading. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1051581
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051581