Search Results for author: Zhengyong Jiang

Found 6 papers, 0 papers with code

A novel multi-agent dynamic portfolio optimization learning system based on hierarchical deep reinforcement learning

no code implementations12 Jan 2025 Ruoyu Sun, Yue Xi, Angelos Stefanidis, Zhengyong Jiang, Jionglong Su

As a result, the DRL agents cannot explore the dynamic portfolio optimization policy to improve the risk-adjusted profitability in the training process.

Deep Reinforcement Learning Portfolio Optimization

YNetr: Dual-Encoder architecture on Plain Scan Liver Tumors (PSLT)

no code implementations30 Mar 2024 Wen Sheng, Zhong Zheng, Jiajun Liu, Han Lu, Hanyuan Zhang, Zhengyong Jiang, Zhihong Zhang, Daoping Zhu

Concurrently, we utilized Dice coefficient as the metric for assessing the segmentation outcomes produced by YNetr, having advantage of capturing different frequency information.

Segmentation

Combining Transformer based Deep Reinforcement Learning with Black-Litterman Model for Portfolio Optimization

no code implementations23 Feb 2024 Ruoyu Sun, Angelos Stefanidis, Zhengyong Jiang, Jionglong Su

However, typical DRL agents for portfolio optimization cannot learn a policy that is aware of the dynamic correlation between portfolio asset returns.

Deep Reinforcement Learning Portfolio Optimization

CAD: Clustering And Deep Reinforcement Learning Based Multi-Period Portfolio Management Strategy

no code implementations2 Oct 2023 Zhengyong Jiang, Jeyan Thiayagalingam, Jionglong Su, Jinjun Liang

To the best of our knowledge, our approach is the first to combine clustering methods and reinforcement learning methods for portfolio management in the context of multi-period trading.

Clustering Deep Reinforcement Learning +2

A Deep Deterministic Policy Gradient-based Strategy for Stocks Portfolio Management

no code implementations21 Mar 2021 Huanming Zhang, Zhengyong Jiang, Jionglong Su

We compare the compound annual return rate of our strategy against seven other strategies, e. g., Uniform Buy and Hold, Exponential Gradient and Universal Portfolios.

Management

Application of Deep Q-Network in Portfolio Management

no code implementations13 Mar 2020 Ziming Gao, Yuan Gao, Yi Hu, Zhengyong Jiang, Jionglong Su

This paper will introduce a strategy based on the classic Deep Reinforcement Learning algorithm, Deep Q-Network, for portfolio management in stock market.

Deep Reinforcement Learning Face Recognition +3

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