Polymarket Trading Bot

Python Polymarket arbitrage bot for BTC, ETH, XRP, and SOL prediction markets. Five parallel strategies - intra-market, combinatorial, cross-platform, endgame, and momentum/mean-reversion - with composite signal ranking and independent risk controls.

Polymarket Trading Bot
Prediction Markets
Blockchain Fullstack
Polymarket Trading Bot - Casatrick Rust / smart contract project screenshot
Status: Active

Project Overview

Python Polymarket arbitrage bot for BTC, ETH, XRP, and SOL prediction markets. Five parallel strategies - intra-market, combinatorial, cross-platform, endgame, and momentum/mean-reversion - with composite signal ranking and independent risk controls.

A Python Polymarket arbitrage bot for BTC, ETH, XRP, and SOL prediction markets. Five strategies run in parallel - intra-market, combinatorial, cross-platform, endgame, and momentum/mean-reversion - with composite signal ranking and independent risk controls.

The bot scans crypto prediction markets, ranks signals by expected edge and strategy priority, and executes through the Polymarket CLOB API on Polygon. Risk limits (position caps, daily loss, consecutive-loss protection) are enforced outside strategy logic so bad signals cannot bypass guards.

Technical Implementation

Architecture

A modular architecture cleanly separating on-chain programs, low-latency data ingestion, and the user-facing app. On-chain code is written in Rust or Solidity with strict test coverage; off-chain services run on Node.js / Rust backends with Redis and PostgreSQL for hot and durable state respectively, containerized for reproducible deploys.

Smart Contracts

Programs are implemented in Rust with the Anchor framework on Solana, or in Solidity on EVM chains, with strict access control, exhaustive error handling, and gas / compute-unit optimization. Every state transition is covered by unit and integration tests before mainnet deployment.

Performance & Reliability

Where the project is performance-sensitive, the hot path is optimized end-to-end: zero-copy parsing, connection pooling, Redis-backed caches, Jito / Nozomi inclusion for Solana, and careful batching for EVM. Monitoring and alerts cover latency, inclusion rate, and PnL so regressions surface immediately.