Financial Data for Portfolio Management

该数据集包含了五种不同技术资产的开盘价、最高价、收盘价和最低价（OHCL）信息，用于训练深度强化学习（DRL）智能体进行投资组合管理。此外，数据集还包括了特征重要性度量以及使用SHAP和LIME方法的结果，以增强DRL智能体预测的可解释性。在规模上，该数据集涉及五种技术资产，状态空间中总共包含20个特征。任务方面，该数据集旨在通过深度强化学习进行投资组合管理和投资决策。

This dataset contains Open, High, Close, and Low (OHCL) data for five distinct technical assets, and is developed for training deep reinforcement learning (DRL) AI Agents to conduct portfolio management. Additionally, the dataset also provides feature importance metrics alongside the results derived from SHAP and LIME methodologies, aiming to improve the interpretability of the DRL AI Agent's predictive outputs. In terms of scale, this dataset involves five technical assets and includes a total of 20 features within its state space. For its targeted tasks, this dataset is designed to support portfolio management and investment decision-making through deep reinforcement learning.