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Data_Management.md

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graph LR
    Core_Engine_Framework["Core Engine/Framework"]
    Strategy_Components["Strategy Components"]
    Data_Management_Layer["Data Management Layer"]
    Reporting_and_Visualization["Reporting and Visualization"]
    Utilities_and_Helpers["Utilities and Helpers"]
    Core_Engine_Framework -- "executes" --> Strategy_Components
    Core_Engine_Framework -- "provides results to" --> Reporting_and_Visualization
    Data_Management_Layer -- "provides data to" --> Core_Engine_Framework
    Strategy_Components -- "operates on" --> Data_Management_Layer
    Core_Engine_Framework -- "uses" --> Utilities_and_Helpers
    Strategy_Components -- "uses" --> Utilities_and_Helpers
    Data_Management_Layer -- "uses" --> Utilities_and_Helpers
    Reporting_and_Visualization -- "uses" --> Utilities_and_Helpers
    click Reporting_and_Visualization href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/bt/Reporting_and_Visualization.md" "Details"
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Details

The bt project, a Domain-Specific Framework/Library for Quantitative Finance Backtesting, is structured around a modular and data-driven architecture.

Core Engine/Framework

The central orchestrator of the backtesting process. It manages the overall execution flow, defines the core logic for running simulations, and coordinates interactions between strategy components and data.

Related Classes/Methods:

Strategy Components

Encapsulates various trading algorithms and investment strategies. These components define the specific rules and logic that dictate how trading decisions are made based on market data during a backtest.

Related Classes/Methods:

Data Management Layer

Handles the ingestion, processing, cleaning, and provision of historical financial data. This component ensures data quality, proper alignment, and availability for the Backtesting Engine to execute strategies.

Related Classes/Methods:

  • bt/data.py (1:1)

Reporting and Visualization [Expand]

Generates comprehensive reports and interactive visualizations of backtest results. This component transforms raw performance metrics into actionable insights, aiding in strategy analysis and evaluation.

Related Classes/Methods:

  • bt/report.py (1:1)
  • bt/chart.py (1:1)

Utilities and Helpers

A collection of common functions, helper classes, and reusable modules that provide foundational support and shared functionalities across various components of the framework.

Related Classes/Methods:

  • bt/utils.py (1:1)

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