10 Industrial Portfolios

该数据集涵盖了10个行业部门的日回报率，将这些部门视为投资组合优化的独立资产。数据集被划分为400天用于训练，100天用于验证，以及100天用于测试。在预测模型中，将过去30天的日回报率作为输入特征。该数据集涉及10个资产，时间跨度为500天，任务是实现均值-方差投资组合优化。

This dataset contains daily returns of 10 industry sectors, which are treated as individual assets for portfolio optimization. The dataset is split into three subsets: 400 days for training, 100 days for validation, and 100 days for testing. For the predictive model, the daily returns of the past 30 days are used as input features. This dataset involves 10 assets with a time span of 500 days, and the task is to perform mean-variance portfolio optimization.