Join traders, quants, and complete beginners using Python for algorithmic trading, market data analysis, and quant finance.
This repository contains the code for the PyQuant Newsletter. Each issue focuses on practical, implementation-ready Python techniques for quantitative finance, algorithmic trading, factor research, portfolio construction, and data engineering. You can subscribe to the PyQuant Newsletter on Substack free.
The PyQuant Newsletter gives you applied quant finance in a compact format designed for working professionals:
- Hands-on code: Each issue includes runnable Python examples for immediate use.
- Actionable quant ideas: Factor signals, trading edges, vol modeling, portfolio techniques, data pipelines.
- Practical focus: Real workflows used by quants, traders, and data scientists.
- Time-efficient: Designed so readers can extract value in ~5 minutes.
- Trusted by practitioners: Read by tens of thousands of quants, traders, engineers, and analysts.
An Alpha Lab membership is for members who want access to backtested strategies and higher-touch interaction.
Every month Alpha Lab members receive a full research deep dive, including:
- Python code for signal construction
- Backtests and performance analysis
- Interpretation of edge, risk, and failure modes
- A reproducible research notebook
- Reversion Strength — identifies exhaustion points where price is likely to revert
- Trend Persistence — rewards assets with sustained directional strength
- Stability Premium — prioritizes assets with persistent, lower-volatility behavior
Alpha Lab members can initiate new discussion threads inside the private chat environment, enabling:
- Direct Q&A
- Strategy-specific help
- Environment setup guidance
- More detailed and open-ended discussions
You can support also PyQuant News and get deeper support, updated code, and access to private discussions through a paid membership.
Access to the Substack Chat, a private channel where members can get personalized help with:
- Python code issues
- Strategy design
- Backtesting workflows
- Execution logic
- Troubleshooting library breaks and environment issues
Note: Only Alpha Lab members can start new chat threads. Paid members can reply and participate.
Python libraries evolve, dependencies break, and tutorials need maintenance. Paid members receive:
- Updated notebooks
- Rewritten code when APIs change
- Fixes for breaking library updates
- Continuously maintained examples that keep running over time
Every newsletter ends with a members-only comments section.
Paid members get:
- Direct interaction
- Thoughtful replies
- Deeper discussions around implementation and research decisions
The newsletter and membership benefits serve:
- Quants and quant-curious developers
- Systematic traders
- Data scientists working with market data
- Python programmers learning quant techniques
- Researchers exploring factor models and trading strategies
If you find this code useful, consider subscribing to receive future issues and member-only benefits.