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学术讲座丨宗翔宇:应用深度强化学习的大宗商品期货配对交易策略研究
发布时间:2023-04-20 09:30:00 浏览次数:2043

数字技术与经济金融学术午餐会(第17期)

 

主讲人:

宗翔宇 博士、研究员

中南财经政法大学金融学院

数字技术与现代金融学科创新引智基地

主持人:

许泳昊博士、研究员

中南财经政法大学金融学院

数字技术与现代金融学科创新引智基地

时间

2023425日(周二)12:00-13:30

地点

文泉楼南508会议室

 

摘要:

Pairs trading is an important strategy in hedge funds. The arbitrage opportunities of this strategy have shrunk over recent years due to its broad application and the constraints of conventional approaches. This project aims to address the limitation of conventional pairs trading strategies that can only use the linear correlation deviation and regression between asset prices. A novel quantitative trading approach is proposed in this project based on a Deep Reinforcement Learning algorithm framework. The main research contents are as follows: (1) using genetic algorithms to optimize the trading threshold in traditional pairs trading strategies to examine the full potential of conventional pairs trading strategies; (2) introducing a Deep Reinforcement Learning-pairs trading model to solve four key issues: reward function design, Deep Reinforcement Learning brain network structure design, invalid training problem, and computational complexity problem; (3) conduct the empirical analyses for different commodity pairs in both domestic market and global market. Meanwhile, this project solves the problem of multi-asset pairing and investigates the impact of pre-selection on the Deep Reinforcement Learning model.

 

主讲人介绍:

宗翔宇,英国格拉斯哥大学亚当斯密商学院博士。从事机器学习,复杂系统理论与量化交易等方向的研究工作。在Energy EconomicsEconomic Modelling, Finance Research Letters等国际期刊上发表过机器学习和复杂系统理论相关论文,并担任多个国际一流期刊匿名审稿人。

 

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