In this tutorial, I walk you through how to backtest a trading strategy in Python with stop loss, take profit, and position sizing.

This builds on concepts from a previous video, where we covered the basics of setting up a simple backtest in Python.

If you haven't seen that one yet, you can watch it here:    • How to Backtest a Trading Strategy in Pyth...  

In this video, we take things a step further by adding basic risk management to make your backtests more realistic and practical. Whether you're just starting with algorithmic trading or looking to improve your current backtesting framework, this guide will help you write cleaner and smarter trading logic in Python.

*What you'll learn in this video*
How to add stop loss and take profit conditions to your backtest
How to calculate position size based on risk per trade
How to simulate trade entries and exits
How to track account balance over time
How to analyze your trade results with a basic equity curve

If you find this helpful, feel free to like, subscribe, and leave a comment with questions or ideas for future videos.

*Chapters*
00:00 Intro
00:15 Recap
01:20 Generate Trade Signals
02:30 Add SL and TP
05:25 Iterative Backtest Logic
12:50 Position Sizing
14:20 Equity Curve
15:05 Flexible SL and TP

#pythontrading #backtesting #tradingstrategy #pandas #algorithmictrading