Abstract
The pairs trading strategy involves selecting two highly correlated securities to profit from mean reversion. However, the traditional simple threshold method is subjective, random, and ignores nonlinear relationships. This paper proposes a new cointegration deep reinforcement learning (DRL) pairs trading model applied to Dalian Commodity Exchange futures to capture nonlinear relationships and gain profits. The CA-DRL model outperforms other models in terms of efficiency and performance.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.