trading
How to Build a Polymarket Arbitrage Bot in Python
Quantitative Trading
System track
Production trading systems under real market constraints.
Prediction-market automation, signal pipelines, and the operational math behind live trading systems.
Guided track Machine-readable 6 posts
Why this cluster exists
Trading systems are only interesting if they survive production. This cluster is about execution, robustness, and market reality.
System object
signal matrix
Best for
quantitative builders and trading-system operators
Start here
The best first read in this track.
Core journey
Read these in order if you want the strongest mental model.
Foundation
The Cross-Market Signal Pipeline That Spots Price Moves Early
Build a Binance-to-Polymarket trading pipeline: real-time signal detection, deduplication, and sub-100ms order execution for momentum trading.
Kalshi vs Polymarket for bot builders
Kalshi vs Polymarket for bot builders, from someone who built on both. US access, Polymarket US, API auth, fee math, demo tests, liquidity. Checked 10/10/2026.
Deep dive
Kalshi fees explained, with a fee calculator
Kalshi fees in one formula, with worked examples at 5 to 95 cents, maker fees, break-even win rates and withdrawal costs, checked against the fee schedule.
Kalshi API in Python: auth, markets and your first order
How I call the Kalshi API from Python: signed requests, market tickers and prices, then a first limit order on the demo exchange, with code I ran.
Applied / adjacent