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boatwright documentation
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boatwright documentation

Contents:

  • Installation
  • Introduction
  • Examples
    • Strategy Example
    • Collect Historical Data
    • Backtest Example
    • Bollinger Bands Example
    • Parameter Scan Example
    • Active Optimization Example
    • Portfolio Backtest Example
    • Incorporating Indicators from TAlib
  • Computational Performance
  • Modules
    • Data
      • Collection
        • Historical Data Collection
          • AlpacaCollector
          • CoinbaseCollector
        • Live Data Collection
          • Coinbase DataStream
      • CSV Database
    • Technical Indicators
      • Moving Averages
      • Logical Comparisons
      • minimum and maximum signals
      • Polynomial Fitting
      • Traditional Indicators
      • Hindsight Optimal Position
    • Strategy
    • Brokers
      • BacktestBroker
      • CoinbaseBroker
      • AlpacaBroker
    • Orders
    • Backtest
    • Live Execution
    • Optimizations
      • ParameterScan
    • ActiveOptimization
    • PortfolioBacktest
    • Performance Metrics
      • Return On Investment
      • Percent Profit
      • Max Drawdown
      • Sharpe Ratio
    • External Interfaces
      • Alpaca Market Data SDK
      • Alpaca Trading SDK
      • Coinbase Advanced SDK
    • BacktestExecutors
      • ParallelExecutor
      • SequentialExecutor
    • Visualization
      • Plot Backtest
      • Parameter Scan 1D analysis
      • Parameter Scan Stack AUM
      • Plot Live Execution
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boatwrightΒΆ

boatwright is a python package for developing and deploying, Backtested & Optimized Automated Trading Strategies (BOATS). New users are encouraged to review the Introduction, and Examples

Contents:

  • Installation
  • Introduction
  • Examples
  • Computational Performance
  • Modules

Indices and tables:

  • Index

  • Module Index

  • Search Page

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Copyright © 2023, Jonathan Van Blarcum
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