Resources¶

Here's a collection of resources to get started.

Notebooks¶

• Performance analysis of Moving Average Crossover
• Performance analysis of stop signals
• Backtesting per trading session
• Portfolio optimization
• Plotting MACD parameters as 3D volume
• Walk-forward optimization
• Running Telegram signal bot
• Porting RSI strategy from backtrader
• Pairs trading (vs backtrader)

Note: you must run the notebook to play with the widgets.

Dashboards¶

• Detecting and backtesting common candlestick patterns

Articles¶

• Stop Loss, Trailing Stop, or Take Profit? 2 Million Backtests Shed Light
• SuperFast SuperTrend
• The PyQuant Newsletter
  • 1,000,000 backtest simulations in 20 seconds

Books¶

• Python for Algorithmic Trading Cookbook: Recipes for designing, building, and deploying algorithmic trading strategies with Python

Getting Help¶

• For questions on Numba and other parts, the best place to go to is StackOverflow
• If you have general questions, start a new GitHub Discussion
• If you found what appears to be a bug, please create a new issue