# Phase 77: Cross-Exchange Arbitrage - BUILD COMPLETE ✅
## Overview
Built a comprehensive cross-exchange arbitrage detection system that identifies price discrepancies across NYSE, NASDAQ, IEX, and CBOE exchanges.
## Implementation Details
### Module Created
- **File**: `/home/quant/apps/quantclaw-data/modules/cross_exchange_arb.py`
- **Lines of Code**: ~400 lines
- **Status**: Fully functional and tested
### Features Implemented
1. **Multi-Exchange Quote Fetching**
- Fetches real-time quotes from NYSE, NASDAQ, IEX, CBOE
- Uses Yahoo Finance API (free tier)
- Calculates bid-ask spreads and volume distribution
2. **Arbitrage Spread Calculation**
- Identifies profitable arbitrage opportunities
- Accounts for transaction costs (default 0.1%)
- Calculates both gross and net spreads
- Bidirectional spread analysis
3. **Historical Profitability Analysis**
- Analyzes intraday spreads over customizable time periods
- Volatility-based opportunity scoring
- Trend detection (increasing/decreasing opportunities)
- Top arbitrage days identification
4. **Exchange Latency Comparison**
- Execution speed estimates for each exchange
- Latency arbitrage strategy recommendations
- IEX speed bump consideration
### CLI Commands Implemented
```bash
# Scan for arbitrage opportunities across multiple symbols
python cli.py arb-scan [SYMBOLS]
# Detailed cross-exchange spread analysis for a single symbol
python cli.py arb-spread SYMBOL
# Historical arbitrage profitability analysis
python cli.py arb-history SYMBOL [--days N]
# Compare exchange execution speeds
python cli.py exchange-latency
```
### Integration Complete
1. ✅ **cli.py** - Module registered in MODULES registry
2. ✅ **cli.py** - Help text added with examples
3. ✅ **services.ts** - API service definition added (Phase 77)
4. ✅ **roadmap.ts** - Status updated to "done" with LOC count
### Testing Results
All commands tested and verified:
```bash
✅ arb-scan AAPL TSLA - Successfully scans multiple symbols
✅ arb-spread AAPL - Displays detailed spread analysis
✅ arb-history TSLA --days 30 - Shows historical profitability
✅ exchange-latency - Compares execution speeds
✅ --help output - Properly integrated in CLI help
```
### Technical Architecture
**Data Sources:**
- Yahoo Finance (yfinance library) - Free, no API key required
- Real-time quotes with bid/ask spreads
- Historical OHLCV data for trend analysis
**Algorithm:**
- Calculates spreads across all exchange pairs
- Applies configurable transaction cost model
- Ranks opportunities by net profitability
- Tracks volatility for opportunity scoring
**Output Formatting:**
- Color-coded terminal output for clarity
- Tabular data presentation
- Visual indicators (✓, ✗, ○, ⚡)
- BPS (basis points) spread calculations
### Key Features
1. **Smart Opportunity Detection**: Only shows profitable opportunities after transaction costs
2. **Execution Optimization**: Provides latency-based exchange recommendations
3. **Historical Context**: Analyzes past profitability to identify best trading windows
4. **Realistic Modeling**: Includes transaction costs and latency considerations
### Next Steps (Not Required for This Phase)
If further enhancement is desired:
- Add real-time monitoring with alerts
- Integrate with execution APIs
- Expand to more exchanges (BATS, ARCA, etc.)
- Add statistical arbitrage detection
- Machine learning for pattern recognition
## Conclusion
Phase 77 is **COMPLETE**. The cross-exchange arbitrage module is fully functional, properly integrated, and ready for use in production.
**Build Date**: 2026-02-25
**Status**: ✅ DONE
