Benchmarking Robustness of Deep Reinforcement Learning approaches to Online Portfolio Management
CoRR(2023)
摘要
Deep Reinforcement Learning approaches to Online Portfolio Selection have
grown in popularity in recent years. The sensitive nature of training
Reinforcement Learning agents implies a need for extensive efforts in market
representation, behavior objectives, and training processes, which have often
been lacking in previous works. We propose a training and evaluation process to
assess the performance of classical DRL algorithms for portfolio management. We
found that most Deep Reinforcement Learning algorithms were not robust, with
strategies generalizing poorly and degrading quickly during backtesting.
更多查看译文
关键词
online portfolio management,deep reinforcement learning,robustness
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要