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Build an OOP Event-Driven Backtester in Python
If you’ve dabbled in algorithmic trading, you know the critical importance of backtesting. I remember my early days, hacking together scripts that quickly became tangled messes — hard to modify, harder to trust. Testing a new idea meant significant rework and simulating realistic conditions felt like guesswork. That’s why we’re diving deep in this tutorial. We’re not just building a backtester; we’re constructing a sophisticated, event-driven system using Object-Oriented Programming (OOP) in Python.
This guide is designed for Python users who are comfortable with OOP principles and want to build a robust framework for evaluating trading strategies. Our goal is to create a system that’s modular, reusable and simulates trading conditions with greater realism than simpler approaches. We’ll focus on separating concerns — data handling, strategy logic, portfolio management and execution simulation will all be distinct, communicating components. This OOP structure is key to building something flexible enough to adapt and grow with your trading ideas. Forget brittle scripts; think robust, reusable building blocks.
Table of Contents
- Foundation: Event-Driven Architecture and Core OOP Components: Understanding the OOP and event-driven design for backtesting.
- Setting Up the Environment and Robust…
