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JACIII Vol.13 No.6 pp. 691-696
doi: 10.20965/jaciii.2009.p0691
(2009)

Paper:

Acquiring a Government Bond Trading Strategy Using Reinforcement Learning

Tohgoroh Matsui*, Takashi Goto**, and Kiyoshi Izumi***

*Tohgoroh Machine Learning Research Institute, Chiba, Japan

**The Bank of Tokyo-Mitsubishi UFJ, Ltd., Tokyo, Japan

***National Institute of Advanced Industrial Science and Technology, Tokyo, Japan

Received:
April 20, 2009
Accepted:
July 31, 2009
Published:
November 20, 2009
Keywords:
machine learning, reinforcement learning, finance, trading strategy
Abstract

This paper proposes using reinforcement learning to acquire a government bond trading strategy. We applied this method to the 10-year Japanese government bond (JGB) market and confirmed that it acquires profitable trading even in extrapolation.

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Last updated on Oct. 20, 2017