Deep Reinforcement Learning for Asset Allocation: Reward Clipping

2023-01-02 · Jiwon Kim, Moon-Ju Kang, KangHun Lee, HyungJun Moon, Bo-Kwan Jeon

Recently, there are many trials to apply reinforcement learning in asset allocation for earning more stable profits. In this paper, we compare performance between several reinforcement learning algorithms - actor-only, actor-critic and PPO models. Furthermore, we analyze each models' character and then introduce the advanced algorithm, so called Reward clipping model. It seems that the Reward Clipping model is better than other existing models in finance domain, especially portfolio optimization - it has strength both in bull and bear markets. Finally, we compare the performance for these models with traditional investment strategies during decreasing and increasing markets.

📄 PDF Abstract BibTeX arXiv:2301.05300

Code (0)

등록된 구현이 없습니다.

Tasks

Deep Reinforcement LearningPortfolio Optimization reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Methods 이 논문이 사용한 방법론

Entropy Regularization 설명 없음

PPO Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable…

Combining Reinforcement Learning and Inverse Reinforcement Learning for Asset Allocation Recommendations

2022-01-06 · Igor Halperin, Jiayu Liu, Xiao Zhang

We suggest a simple practical method to combine the human and artificial intelligence to both learn best investment practices of fund managers, and provide recommendations to improve them. Our approach is based on a comb…

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Deep Reinforcement Learning for Asset Allocation in US Equities

2020-10-09 · Miquel Noguer i Alonso, Sonam Srivastava

Reinforcement learning is a machine learning approach concerned with solving dynamic optimization problems in an almost model-free way by maximizing a reward function in state and action spaces. This property makes it an…

Deep Reinforcement Learning Management reinforcement-learning Reinforcement Learning+4

Deep Reinforcement Learning for Optimal Asset Allocation Using DDPG with TiDE

2025-08-12 · Rongwei Liu, Jin Zheng, John Cartlidge arxiv

The optimal asset allocation between risky and risk-free assets is a persistent challenge due to the inherent volatility in financial markets. Conventional methods rely on strict distributional assumptions or non-additiv…

Reinforcement Learning

Asset Allocation: From Markowitz to Deep Reinforcement Learning

2022-07-14 · Ricard Durall

Asset allocation is an investment strategy that aims to balance risk and reward by constantly redistributing the portfolio's assets according to certain goals, risk tolerance, and investment horizon. Unfortunately, there…

Deep Reinforcement Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Generalisation of RLHF under Reward Shift and Clipped KL Regularisation

2026-02-25 · Kenton Tang, Yuzhu Chen, Fengxiang He arxiv

Alignment and adaptation in large language models heavily rely on reinforcement learning from human feedback (RLHF); yet, theoretical understanding of its generalisability remains premature, especially when the learned r…