Combining Multiple Kernel Learning and Genetic Algorithm for forecasting short time foreign exchange rate

Shangkun Deng, Akito Sakurai

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

This paper proposes a hybrid model named MKL-GA, which combines Multiple Kernel Learning (MKL) and Genetic Algorithm (GA), for modeling and the prediction of FX (foreign exchange) rate on USDJPY currency pair by extracting features from three main FX pairs with three different short time horizons. Firstly, the MKL regression model predicts the change rate based on MACD indicators, and then GA is applied to fuse all the information from the regression model and overbought/oversold technical indicators. Experimental results show that the proposed model outperforms other models in terms of returns and risk-return ratio. In addition, the result of kernel weights for different currency pairs in the step of MKL training should be also advisable for the trading.

本文言語English
ホスト出版物のタイトルProceedings of the 11th IASTED International Conference on Artificial Intelligence and Applications, AIA 2011
ページ200-209
ページ数10
DOI
出版ステータスPublished - 2011
イベント11th IASTED International Conference on Artificial Intelligence and Applications, AIA 2011 - Innsbruck, Austria
継続期間: 2011 2月 142011 2月 16

出版物シリーズ

名前Proceedings of the 11th IASTED International Conference on Artificial Intelligence and Applications, AIA 2011

Other

Other11th IASTED International Conference on Artificial Intelligence and Applications, AIA 2011
国/地域Austria
CityInnsbruck
Period11/2/1411/2/16

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ サイエンスの応用

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