🎯 New Tool Drop: Polymarket Arbitrage Bot (Pure Alpha Strategy)

Just finished building something I think you'll find interesting - a fully automated arbitrage bot for Polymarket prediction markets. This isn't your typical degen play - it's a mathematically sound, market-neutral strategy that profits from pricing inefficiencies.

🧠 The Core Strategy

The bot exploits a simple mathematical truth: in any binary market (YES/NO), the prices must sum to $1.00 because exactly one outcome will happen.

When YES + NO < $1.00 = Risk-Free Profit

Real example:

BTC to hit $100K: YES @ $0.42, NO @ $0.55

Sum: $0.97 (you're paying 97¢ for a guaranteed $1.00)

Buy 100 shares of each = $97 cost → $100 payout = $3 profit (3.1% return)

But here's where it gets interesting...

🎲 The "Smart Overload" Edge

Instead of just pure arbitrage, the bot runs an internal probability model using Black-Scholes math to detect which side is actually mispriced:

If market says YES = 42% but model calculates 38%

→ YES is overpriced by 4%

→ Overweight the NO side (60/40 or 70/30 allocation)

This turns simple arbitrage into positive expected value trades while maintaining downside protection.

⚡ What Makes This Different

Speed Matters:

Direct WebSocket feeds from Polymarket CLOB

NumPy-optimized order book processing

Private RPC endpoints (public ones are too slow)

Can detect and execute arbs in <500ms

Risk Controls Built In:

Automatic kill switch on oracle delays

Max 80% allocation to one side (always hedged)

Daily loss limits (15% default)

Per-trade position sizing via Kelly Criterion

Handles orphaned positions automatically

Production-Ready:

EIP-712 order signing

Batch execution (up to 15 orders/call)

Redis caching for state management

Rate limiting with token bucket algorithm

Full paper trading mode

💰 Capital Requirements

Minimum to run:

50+ MATIC for gas (~$20-30)

Starting capital in USDC.e (recommend $500-1000)

Private RPC endpoint (Alchemy/Infura - free tier works)

Expected returns:

Pure arb spreads: 1-5% per trade

With overload: 3-15% per trade

Target: 15-30% monthly (depends on market activity)

🛠️ Tech Stack

Python 3.11+ (async/await architecture)

Redis for caching

Web3.py for Polygon interactions

Polymarket CLOB API + Binance for spot prices

Runs on any VPS (closer to NYC = lower latency)

📊 Real Example Workflow

Bot scans 15+ active markets simultaneously

Detects BTC $100K market: YES (0.42) + NO (0.55) = 0.97

Calculates fair value via internal model: 38% / 62%

Decides on 65/35 overload (favoring NO)

Signs and submits batch order

Tracks fills, manages position

Market resolves → calculates PnL

⚠️ Real Talk (Risks)

Not passive income - requires monitoring, especially in live mode

Slippage exists - small markets have thin liquidity

Oracle risk - if Binance feed lags, kill switch activates

Smart contract risk - you're interacting with Polymarket CTF contracts

Regulatory gray area - prediction markets have unclear status in some jurisdictions

🚀 Getting Started

The documentation includes:

Complete setup guide (wallet, APIs, RPC endpoints)

Paper trading mode (test with fake money first)

Step-by-step deployment path

Troubleshooting common issues

Full architecture breakdown

Recommended path:

Week 1: Paper trade 24/7, review logs daily

Week 2: Deploy with $100 real capital

Week 3: Scale to $500 if profitable

Month 2+: Gradually increase based on performance

📚 What You'll Learn

Even if you don't run the bot, the codebase is a masterclass in:

Market-making and arbitrage mechanics

Real-time data processing at scale

Production DeFi bot architecture

Risk management systems

Order book analysis with NumPy

🤝 Who This Is For

✅ You understand basic options/probability math

✅ Comfortable with Python and command line

✅ Have capital you can afford to tie up/risk

✅ Interested in systematic, not discretionary trading

✅ Want to learn by building/running real strategies

❌ Looking for "set and forget" passive income

❌ Expect 100%+ monthly returns

❌ Not comfortable with code or debugging

❌ Can't afford the time to monitor and optimize

💭 My Take

This is the most "boring" profitable strategy I know - and I mean that as the highest compliment. No chart reading, no fundamentals analysis, no Twitter alpha. Just pure math and speed.

The edge is simple: most Polymarket users are retail traders operating manually. An automated system with millisecond reaction times and proper risk controls will consistently capture small edges that add up.

Is it going to 10x your account? No.

Will it generate consistent, relatively low-risk returns if markets are active? Based on backtesting and paper trading - yes.

📥 Access

The full documentation includes:

Complete technical specification

Setup guide with every API credential explained

Usage guide with monitoring tips

Architecture deep-dive

Risk management framework

Drop a comment if you're interested and I'll share the docs + repo. Also happy to answer questions about the strategy, implementation, or help troubleshoot if anyone deploys it.

Disclaimer: This is educational content. Trading involves financial risk. Prediction markets may have regulatory restrictions in your jurisdiction. Always start with paper trading. Never risk capital you can't afford to lose. I'm not a financial advisor, just a degen who likes building systematic strategies.

Who's running bots in prod right now? What strategies are you trading? Let's compare notes 👇

Github Repo:

https://github.com/defiuniversity-xyz/poly-stat-blue

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