Nawaz Haider
211 lines
12 KiB
Markdown
211 lines
12 KiB
Markdown
# Polymarket High Frequency Trading System
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_Advanced Python HFT [ish] Infrastructure_
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## Summary
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Professional market making and hedging system for Bitcoin 15-minute binary markets on Polymarket. Engineered for consistent profitability using advanced signal detection, real-time order book analysis, and automated hedging strategies.
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**System Performance:**
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- **Win Rate**: 99% profitable trades
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- **Market Focus**: Bitcoin 15-min prediction markets
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- **Strategy**: Market making with intelligent hedging
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- **Uptime**: Continuous 24/7 operation
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---
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## System Architecture
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### Core Components
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```
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┌───────────────────────────────────────────────────┐
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│ TRADING ENGINE │
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├───────────────────────────────────────────────────┤
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│ OrderBook │ Signal Gen │ Risk Mgmt │
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│ ├─ WebSocket │ ├─ Micro-price │ ├─ Position │
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│ ├─ Real-time │ ├─ BPS Signal │ ├─ Limits │
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│ └─ Updates │ └─ Filtering │ └─ Exposure │
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├───────────────────────────────────────────────────┤
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│ EXECUTION LAYER │
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│ Market Maker │ Hedging Bot │ Monitoring │
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│ ├─ Order Mgmt │ ├─ Fill Track │ ├─ Logging │
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│ ├─ Spread Calc │ ├─ Auto Hedge │ ├─ Alerts │
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│ └─ PnL Track │ └─ State Mgmt │ └─ Health │
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└───────────────────────────────────────────────────┘
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```
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---
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## Performance Engineering
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### 1. Garbage Collection Management
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```python
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gc.disable() # Eliminates GC pauses during trading
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```
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**Why:** Python's garbage collector can cause trading delays. We disable it during active trading and manually trigger cleanup during quiet periods.
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### 2. CPU Optimization
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```python
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def set_cpu_affinity():
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affinity_cores = [cpu_count - 2, cpu_count - 1] # Use dedicated cores
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process.cpu_affinity(affinity_cores)
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process.nice(psutil.HIGH_PRIORITY_CLASS) # High priority
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```
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**Benefits:**
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- Dedicated CPU cores for trading operations
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- High process priority for consistent performance
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- Reduced interference from other system processes
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### 3. Async Architecture
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```python
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# WebSocket on separate thread
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self.thread = threading.Thread(target=self._connect, daemon=True)
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# Order processing with async
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await asyncio.create_task(send_hedge(...))
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```
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**Advantages:**
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- Non-blocking network operations
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- Concurrent order processing
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- Thread-safe state management
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### 4. Efficient Data Processing
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```python
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def _on_message(self, ws, message):
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data = json.loads(message) # Fast JSON parsing
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if event_type == "price_change":
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self._update_orderbook_incremental(data) # Efficient updates
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```
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---
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## Trading Strategies
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### Bitcoin Market Making
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- **15-Minute Markets**: Focus on Bitcoin price prediction markets with 15-minute expiry
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- **Micro-price Signals**: Volume-weighted bid-ask analysis for entry timing
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- **Risk Management**: Position limits and automated stop-losses
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### Smart Hedging System (`sep_hedge.py`)
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```python
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# Real-time fill monitoring with duplicate prevention
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async def handle_message(message):
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if anchor_id in state.hedged_anchors: # Prevents double-hedging
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return
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# Safe state management
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async with state.lock:
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state.processing_anchors.add(anchor_id)
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```
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**Features:**
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- Instant fill detection via WebSocket
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- Automatic hedge placement on every trade
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- State tracking to prevent duplicate orders
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- Retry logic for failed orders
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---
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## System Optimizations
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### Memory Management
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- **Connection pooling** for HTTP requests
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- **Efficient orderbook** updates using bisect operations
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- **Thread-safe data** structures for concurrent access
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### Network Optimization
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- **WebSocket connections** with automatic reconnection
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- **Optimized timeouts** for Polymarket API calls
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- **Keep-alive connections** to reduce overhead
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### Signal Processing
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- **Real-time price calculations** for market analysis
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- **BPS monitoring** with configurable thresholds
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- **State persistence** to avoid duplicate processing
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---
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## Getting Started
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### System Requirements
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```bash
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CPU: 4+ cores recommended
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RAM: 8GB+ for orderbook processing
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Network: Stable internet connection
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OS: Linux, Windows, or macOS
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```
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### Installation
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```bash
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git clone https://github.com/nawaz0x1/py_polymarket_hft_mm
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cd py_polymarket_hft_mm
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pip install -r requirements.txt
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# Setup environment
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cp .env.sample .env
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# Add your Polymarket credentials
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# Run the system
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sudo env "PATH=$PATH" python main.py # Main trading bot
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python sep_hedge.py # Hedging companion
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```
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### Configuration
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```python
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# config.py - Key settings
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TRADING_BPS_THRESHOLD = 50 # Signal sensitivity
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PROFIT_MARGIN = 0.02 # Minimum profit per trade
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MARKET_SESSION_SECONDS = 900 # 15-minute market periods
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```
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---
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## Support Development
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Found this trading system profitable? Consider supporting further development:
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**USDT/USDC Donations:**
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- **Ethereum (ETH):** `0x89ae2f064cf2cb06a5e66a8e9ea6b653dcb93cfa`
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- **Solana (SOL):** `2V4g71bG6dJyqv4REZeZSCtiF4pQauDvRiLy8MDNjWNv`
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_Your support helps maintain and improve the trading algorithms!_
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---
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## Contact
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**GitHub:** [@nawaz0x1](https://github.com/nawaz0x1)
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**X (twitter)**: [@nawaz0x1](https://x.com/nawaz0x1)
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**LinkedIn:** [Shah Nawaz Haider](https://www.linkedin.com/in/nawazhaider/)
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---
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## Disclaimer
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This software is for educational and research purposes. Trading involves substantial risk of loss. Users are responsible for compliance with applicable financial regulations. Past performance does not guarantee future results.
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