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Welcome to AlphaFlow

AlphaFlow is a Python-based, event-driven backtesting framework designed for professional-grade trading research and strategy development. Built on a robust pub-sub architecture, AlphaFlow provides a flexible, high-performance environment for quantitative analysts and algorithmic traders.

Vision: Offer a "batteries included" backtesting experience leveraging the simplicity of Python, while also enabling unlimited customization and optimization using an event-driven architecture that can support components written in any language.

Key Features

  • Event-Driven Core

    • Uses a publish-subscribe (pub-sub) architecture to simulate market data, order placements, and trade executions in a realistic, decoupled manner.
    • Priority-based event queue ensures proper chronological ordering of events.

  • Commission Tracking

    • Built-in commission handling for realistic transaction costs.
    • Customizable broker implementations for different commission structures.

  • Multi-Asset Support

    • Focused on stocks & ETFs with daily or intraday data.
    • Built to extend to futures, forex, cryptocurrencies, and options in future releases.

  • Benchmark Comparison

    • Compare strategy performance against market benchmarks (e.g., SPY for S&P 500).
    • Side-by-side performance visualization.

  • Extendable & Modular

    • Swap out data sources (CSV, Alpha Vantage API, Financial Modeling Prep API, or build your own).
    • Plugin-style architecture for custom brokers, strategies, analytics, and risk management.
    • Components are planned to be made language agnostic in a future release (v1).
    • A solid foundation for live trading integration in a future version (v1).

  • Professional-Grade Analytics

    • Built-in performance metrics: Sharpe ratio, Sortino ratio, maximum drawdown, annualized returns.
    • Customizable analytics modules for specialized reporting.

Coming in Future Releases

AlphaFlow is evolving to become a comprehensive trading platform. Our development focuses on:

  • Realistic Execution: Slippage models, partial fills, latency simulation, and order rejections
  • Multi-Timeframe Support: Mix second, minute, and daily data in a single backtest
  • Advanced Tools: Technical indicators, advanced order types, strategy validation framework
  • Live Trading: Real-time data feeds, paper trading, broker connectivity
  • Operational Excellence: Monitoring, logging, performance optimization
  • Multi-Asset Expansion: Futures, forex, crypto, and options support
  • Machine Learning: First-class ML integration with proper time-series handling

See the Roadmap for more details.

Why AlphaFlow?

  1. Maintainable & Modern
    Many legacy libraries are no longer actively maintained or don’t follow best practices. AlphaFlow focuses on code quality, modular design, and clear APIs.

  2. Powerful & Future-Proof
    By embracing an event-driven architecture, you get fine-grained control over every aspect of your trading simulation. The transition to real-time or live trading is also more natural compared to purely vectorized solutions.

  3. Commission-Aware Backtesting
    Built-in commission tracking ensures realistic transaction costs are accounted for in your strategy performance.

  4. Performance Upgrades
    Future performance optimizations (including potential Rust components for hot paths) will enable large-scale backtests without major slowdowns or memory bottlenecks.

  5. Community & Extensibility
    Built to be plugin-friendly, allowing the community to add new data feeds, brokers, analytics modules, and advanced features without modifying the core.

High-Level Architecture

1. EventBus (Pub-Sub)

  • The heart of AlphaFlow.
  • Components (DataFeed, Strategy, Broker, Portfolio, Analytics) subscribe to and publish events.
  • Ensures a loose coupling: each module only needs to know how to react to specific event types.

2. DataFeed

  • Responsible for providing market data (historical or real-time).
  • Publishes MarketDataEvents (price bars, ticks, earnings, news, etc.) to the EventBus.
  • Can support multiple timeframes (daily, intraday, tick data in v2).

3. Strategy

  • Subscribes to MarketDataEvents from the DataFeed.
  • Generates trading signals and publishes OrderEvents to the Broker.
  • Can also subscribe to Portfolio updates if needed (to track position sizing, risk limits, etc.).

4. Broker (Execution Engine)

  • Subscribes to OrderEvents from the Strategy.
  • Simulates fills (partial or full) and slippage, calculates commissions, and publishes FillEvents.
  • Centralizes order handling logic, making it easy to swap in a real-time broker later.

5. Portfolio

  • Subscribes to FillEvents to track positions, cash balances, and profit/loss.
  • Optionally publishes portfolio updates (like margin calls, risk alerts) to other modules.

6. Analytics

  • Subscribes to relevant events (MarketData, FillEvents, or PortfolioUpdates) to compile performance metrics, visualize PnL curves, or generate custom reports.
  • Encourages real-time or post-backtest reporting, ideal for quick iteration.