Quant Python: Architecting Autonomous Trading Systems
Python QuantThis course moves you from a coder to a Quant Infrastructure Engineer, focusing on high-concurrency execution and robust risk management.In production, a slippage or a WebSocket delay is the difference between a high-performing alpha and a blown account.
| Platform |  | Pricing | Freemium | Publishes | Daily |
|---|---|---|---|---|---|
| Issues | 120 | Founded | 8 months ago | Last Issue | 31 hours ago |
| Active | |||||
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quantpython.substack.comLatest Issues
Day 114 — True Range Foundations: The Bug Hiding Inside a Correct Formula
Every ADX implementation you will ever read gets the math right and the architecture wrong.
Every ADX implementation you will ever read gets the math right and the architecture wrong. This lesson is about the architecture.
Day 113 — Directional Movement: Coding +DM and -DM
The “Independent Threshold” Trap
The “Independent Threshold” Trap
Day 112 — Squeeze Indicator: Combining Volatility and Momentum
The “compute-it-in-pandas-every-tick” trap
The “compute-it-in-pandas-every-tick” trap
Day 111 — TA-Lib Integration: Wrapping C-Based Speed Indicators
The “just call talib.RSI() every tick” trap
The “just call talib.RSI() every tick” trap
Day 110 —ATR Scaling: Measuring “Market Heat” via True Range
The “high minus low” trap
Every junior quant dev implements Average True Range the same way, on the same night, at 11pm, working off a half-remembered TradingView tooltip: pull high and low off the bar, subtract, average over N peri...
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