Polymarket Prediction Bot Case Study: How One Trader Achieved +90% Returns

A disciplined trader turned consistent profits on Polymarket using a focused, rules-based bot. Here’s the technical breakdown.

Strategy Overview

The bot specialized in 15-minute BTC Up/Down markets with a strict End-Cycle approach:

• Entered only in the last 45–90 seconds of each round
• Required minimum 7¢ edge after fees
• Combined:
  • Short-term momentum (15s/30s BTC price action via Binance WebSocket)
  • Order book imbalance
  • Time-decay adjusted probability model

Core Technical Stack

• Data Layer: Binance WebSocket (@aggTrade) + Polymarket CLOB WebSocket
• Probability Engine: XGBoost ensemble + Bayesian update with heavy time-weighting
• Execution: viem on Polygon for direct Conditional Tokens interaction
• Order Type: IOC (Immediate-Or-Cancel) with pre-fill best-ask validation
• Position Sizing: Fractional Kelly with volatility adjustment

Risk Management (The Real Secret)

• Max 1.5% risk per trade
• Daily drawdown limit: -6%
• No trading during high volatility periods
• Auto-pause after 3 consecutive losses
• Strict per-market exposure caps

Results

• +90% return over the tested period
• Win rate ~68% on high-conviction setups
• Survived multiple major BTC swings with minimal drawdown

Key Lesson: 90% returns didn’t come from fancy AI, but from high signal quality, strict edge filtering, and ironclad risk rules.

Most bots fail because they overtrade. This one succeeded by being extremely selective.

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If you have more questions, please feel free to contact me at any time: https://t.me/NevoSayNev0

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Tags: #Polymarket #TradingBots #PredictionMarkets #QuantitativeTrading #DeFi #Web3 #AlgorithmicTrading #Fintech #RiskManagement