Find Arbitrage

Advanced arbitrage opportunity scanner that detects profitable trading opportunities across centralized exchanges (CEX), decentralized exchanges (DEX), cross-chain bridges, and funding rate differentials. Features real-time WebSocket monitoring, gas cost analysis, execution simulation, and comprehensive risk management.

Overview

This command scans multiple markets simultaneously to identify price discrepancies that can be exploited for profit. It supports:

• Cross-Exchange Arbitrage (CEX-CEX): Price differences between Binance, Coinbase, Kraken, and other centralized exchanges
• DEX Arbitrage: Triangular arbitrage on Uniswap, Sushiswap, Curve, and Balancer
• Flash Loan Arbitrage: Zero-capital opportunities using Aave/dYdX flash loans
• Cross-Chain Arbitrage: Bridge opportunities between Ethereum, BSC, Polygon, and Arbitrum
• Funding Rate Arbitrage: Perpetual futures funding rate discrepancies
• Statistical Arbitrage: Mean reversion and correlation-based strategies

Key Features

• Real-Time Detection: WebSocket connections with <100ms latency
• Profitability Analysis: Gas costs, slippage, and fee calculations
• Execution Simulation: Test strategies without risking capital
• Risk Management: Position sizing, stop-loss, and maximum drawdown controls
• Backtesting Framework: Historical performance analysis
• Multi-Chain Support: Ethereum, BSC, Polygon, Arbitrum, Optimism

Architecture

┌─────────────────────────────────────────────────────────────┐
│                  Arbitrage Finder Engine                     │
├─────────────────────────────────────────────────────────────┤
│                                                               │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐      │
│  │  CEX Monitor │  │  DEX Monitor │  │ Bridge Monitor│      │
│  │  (WebSocket) │  │  (RPC Calls) │  │  (API Calls) │      │
│  └──────┬───────┘  └──────┬───────┘  └──────┬───────┘      │
│         │                  │                  │              │
│         └──────────┬───────┴──────────────────┘              │
│                    ▼                                          │
│         ┌──────────────────────┐                             │
│         │  Opportunity Detector │                             │
│         │  - Price Analysis    │                             │
│         │  - Spread Calculation│                             │
│         │  - Gas Estimation    │                             │
│         └──────────┬───────────┘                             │
│                    ▼                                          │
…

Implementation

Complete Arbitrage Scanner (800+ Lines)

#!/usr/bin/env python3
"""
Advanced Arbitrage Opportunity Finder
Supports CEX, DEX, flash loans, cross-chain, and funding rate arbitrage
"""

import asyncio
import json
import time
from typing import Dict, List, Optional, Tuple
from dataclasses import dataclass, field
from decimal import Decimal
from enum import Enum
import websockets
import aiohttp
from web3 import Web3
from web3.middleware import geth_poa_middleware
import ccxt.async_support as ccxt
…

Usage Examples

Basic Opportunity Scan

# Find all arbitrage opportunities
/find-arbitrage

# Filter by minimum profit
/find-arbitrage --min-profit 100

# Filter by risk level
/find-arbitrage --risk low

# Specific arbitrage type
/find-arbitrage --type cex_cex

Real-Time Monitoring

# Start WebSocket monitoring
detector = ArbitrageDetector(['binance', 'coinbase', 'kraken'], rpc_url, eth_price)
await detector.start_monitoring(['BTC/USDT', 'ETH/USDT'])

# Get opportunities in real-time
opportunities = detector.get_top_opportunities(limit=10)

Execution Simulation

# Simulate execution with 0.2% slippage
simulator = ExecutionSimulator()
result = await simulator.simulate_execution(opportunity, slippage_percentage=Decimal('0.2'))

# Get statistics
stats = simulator.get_statistics()
print(f"Success Rate: {stats['success_rate']:.1%}")
print(f"Total Profit: ${stats['total_profit_usd']:.2f}")

Backtesting

# Load historical data
backtest = BacktestEngine(initial_capital=Decimal('10000'))
opportunities = backtest.load_historical_data('opportunities.json')

# Run backtest
metrics = backtest.run_backtest(opportunities, strategy='low_risk_only')

print(f"Total Return: {metrics['total_return_percentage']:.2f}%")
print(f"Win Rate: {metrics['win_rate_percentage']:.1f}%")
print(f"Max Drawdown: {metrics['max_drawdown_percentage']:.2f}%")

Risk Management

Position Sizing

• Maximum Capital Per Trade: 20% of total capital
• Stop Loss: Close position if loss exceeds 2%
• Take Profit: Close 50% at 5% profit, trail remaining

Gas Cost Monitoring

# Set maximum acceptable gas cost
max_gas_usd = Decimal('50')

# Filter opportunities
profitable_opps = [
    opp for opp in opportunities
    if opp.gas_cost is None or opp.gas_cost.cost_usd < max_gas_usd
]

Slippage Protection

# Calculate acceptable slippage
max_slippage = Decimal('0.5')  # 0.5%
min_net_profit = opportunity.gross_profit_usd * (1 - max_slippage / 100)

# Only execute if profitable after slippage
if min_net_profit > opportunity.fees_usd:
    execute_trade(opportunity)

Performance Optimization

WebSocket Connection Pooling

• Maintain persistent WebSocket connections
• Reconnect automatically on disconnection
• Rate limit: 10 messages/second per exchange

Price Cache

• TTL: 1 second for CEX prices
• TTL: 5 seconds for DEX prices