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2 个仓库

Awesome GitHub RepositoriesFinancial Data Engineering

Processes of fetching, cleaning, and transforming raw financial market data into features for model training.

Distinct from Financial Market Data: The candidates are either too specific (Brazilian data) or too broad (general market data streams), not capturing the engineering pipeline.

Explore 2 awesome GitHub repositories matching data & databases · Financial Data Engineering. Refine with filters or upvote what's useful.

Awesome Financial Data Engineering GitHub Repositories

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  • ai4finance-llc/finrlAI4Finance-LLC 的头像

    AI4Finance-LLC/FinRL

    15,518在 GitHub 上查看↗

    FinRL is a financial reinforcement learning framework and quantitative trading library. It provides a specialized system for developing, training, and simulating autonomous agents designed to automate financial trading and portfolio management. The project serves as an automated portfolio optimizer and financial market simulator. It enables the creation of decision-making policies to balance asset allocations, maximize potential returns, and minimize financial risk through reinforcement learning. The framework includes capabilities for financial market data engineering, algorithmic trading s

    Fetches and prepares raw market data into technical indicator datasets for training autonomous trading agents.

    Jupyter Notebook
    在 GitHub 上查看↗15,518
  • hudson-and-thames/mlfinlabhudson-and-thames 的头像

    hudson-and-thames/mlfinlab

    4,835在 GitHub 上查看↗

    mlfinlab 是一个 Python 机器学习库,专为金融领域设计,用于构建和验证量化交易及投资组合管理中使用的模型。它提供了一个金融数据工程工具包和量化策略回测框架,将原始市场数据转换为预测信号和目标类别。 该库包含一个合成金融数据生成器,用于创建模拟真实资产统计特性的合成数据集,以进行压力测试。它还提供了用于金融时间序列标记和采样的专用工具,以防止非平稳市场中的数据泄露。 该项目涵盖了广泛的量化功能,包括特征工程、用于投资组合多元化的资产共依赖分析以及用于资本配置的风险调整后头寸规模确定。它还提供了通过聚类和交叉验证进行模型优化的实用程序,以评估交易策略的稳健性。

    Transforms raw financial market data into target classes and features for model training.

    Pythonalgorithmic-tradingfinancefinancial-machine-learning
    在 GitHub 上查看↗4,835
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  3. Financial Data Engineering

探索子标签

  • Financial ML Data StructuringCreation of specialized data structures and labels tailored for financial machine learning models. **Distinct from Financial Data Engineering:** Focuses specifically on the ML-ready structuring and labeling of data, not just general fetching or cleaning.