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Artwork for Quant Python: Architecting Autonomous Trading Systems

Quant Python: Architecting Autonomous Trading Systems

Python Quant
Tens of paid subscribers

This 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
Substack
PricingFreemiumPublishesDaily
Issues123Founded9 months agoLast Issue9 days ago
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quantpython.substack.com
Artwork for Quant Python: Architecting Autonomous Trading Systems

Latest Issues

Day 117 — Trend Filters: Suppressing Signals When ADX Says "Don't Trust This"

The “Trade Every Crossover” Trap

The “Trade Every Crossover” Trap

9 days ago
1
Paid

Day 116 — Final ADX: Determining Trend Strength Values (0-100)

The “Just Average the DI Spread” Trap

The “Just Average the DI Spread” Trap

13 days ago
1
Paid

Day 115 — Wilder Smoothing: Coding the ADX Decay Model

The “Just Average the Last N” Trap

By Day 115 you’ve already built the hard part. Day 113 gave you mutually exclusive +DM/-DM. Day 114 synchronized TR, +DM, and -DM into a single Wilder RMA substrate so the three legs can’t silently des...

17 days ago
1

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.

21 days ago
Paid

Day 113 — Directional Movement: Coding +DM and -DM

The “Independent Threshold” Trap

The “Independent Threshold” Trap

25 days ago
1
Paid

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