Reporting_and_Visualization.md

graph LR
    Backtest_Result_Data_Model["Backtest Result Data Model"]
    Reporting_Engine["Reporting Engine"]
    Visualization_Engine["Visualization Engine"]
    Backtest_Result_Data_Model -- "provides data to" --> Reporting_Engine
    Backtest_Result_Data_Model -- "provides data to" --> Visualization_Engine
    Reporting_Engine -- "consumes" --> Backtest_Result_Data_Model
    Visualization_Engine -- "consumes" --> Backtest_Result_Data_Model

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Details

The Reporting and Visualization subsystem is crucial for evaluating the effectiveness of trading strategies by presenting backtest results in an understandable format. This subsystem is built around a central data model that encapsulates backtest outcomes, supported by dedicated engines for generating textual reports and graphical visualizations.

Backtest Result Data Model

Encapsulates the comprehensive results of a backtest, including performance metrics, equity curves, and trade details. It provides methods for accessing and preparing this data for reporting and visualization.

Related Classes/Methods:

• bt.backtest.Result
• bt.backtest.Result:get_weights
• bt.backtest.Result:get_security_weights
• bt.backtest.Result:plot_histogram
• bt.backtest.Result:plot_weights
• bt.backtest.Result:_get_backtest

Reporting Engine

Responsible for generating structured, often textual, reports from the backtest results. This includes detailed tables of performance statistics, monthly returns, and other analytical summaries.

Related Classes/Methods:

• bt.report

Visualization Engine

Handles the graphical representation of backtest results, producing charts such as equity curves, drawdowns, histograms, and weight allocations. It leverages plotting libraries to create insightful visual analyses.

Related Classes/Methods:

• bt.chart

FAQ