DOLPHIN/nautilus_dolphin/IMPLEMENTATION_SUMMARY.md

DOLPHIN Nautilus Implementation Summary

Date: 2026-02-18
Status: Phase 3 Complete, Phase 4 Started

---

Implementation Status by Task

Phase 1: Foundation ✅ Complete

• ✅ 1.1 Development Environment Setup (configured in requirements.txt, config.yaml)
• ✅ 1.2 Signal Bridge Actor (signal_bridge.py)
  • Redis Streams consumption with xread
  • Timestamp parsing (seconds/ms/ns)
  • Signal validation with freshness check
  • Error handling and backoff
• ✅ 1.3 Basic Execution Strategy (strategy.py)
  • Signal subscription and filtering
  • Lifecycle methods (on_start/on_stop)
  • SmartExecAlgorithm registration

Phase 2: Core Logic ✅ Complete

• ✅ 2.1 Signal Filtering (volatility_detector.py, strategy.py)
  • VolatilityRegimeDetector with P50/P75 thresholds
  • IRP alignment filter (>=0.45)
  • Direction confirmation filter
  • Momentum magnitude filter (>0.75bps)
  • Asset exclusion (stablecoins)
  • Position limits (max 10 concurrent)
• ✅ 2.2 Dynamic Leverage Calculation (strategy.py)
  • Base formula: min_lev + (strength^convexity) * (max_lev - min_lev)
  • Alpha multipliers: bucket_boost, streak_mult, trend_mult
  • Sanity check (max 50% account balance)
• ✅ 2.3 Position Sizing (strategy.py)
  • Notional calculation: balance * fraction * leverage
  • Quantity conversion with precision
• ✅ 2.4 Exit Logic (position_manager.py)
  • PositionManager class
  • TP condition (99bps for SHORT)
  • Max hold condition (120 bars)
  • Exit execution via SmartExecAlgorithm

Phase 3: Execution ✅ Complete

• ✅ 3.1 SmartExecAlgorithm Entry Orders (smart_exec_algorithm.py)
  • Limit order 1bps inside spread
  • 25s timeout with market fallback
  • NEW: Abort when price moves 5bps against
  • Fill tracking (maker/taker)
• ✅ 3.2 SmartExecAlgorithm Exit Orders (smart_exec_algorithm.py)
  • TP exit: market order
  • Max hold: limit 10s → market fallback
  • Order rejection handler
• ✅ 3.3 Fee and Slippage Measurement (smart_exec_algorithm.py)
  • NEW: Fee tracking (0.02% maker, 0.05% taker)
  • NEW: Slippage calculation (actual vs expected price)
  • NEW: Metrics collection via get_metrics() / reset_metrics()
• ✅ 3.4 Circuit Breakers (circuit_breaker.py)
  • NEW: CircuitBreakerManager class
  • Daily loss limit (10% hard stop)
  • Max concurrent positions (10)
  • Per-asset position limit (1)
  • API failure tracking (3 consecutive)
  • Order size sanity check (50%)
  • Auto-reset after 24 hours
• ✅ 3.5 Metrics Monitor (metrics_monitor.py)
  • NEW: MetricsMonitor class
  • Maker fill rate tracking (1-hour rolling)
  • Slippage tracking (rolling average)
  • Funding rate tracking (24-hour)
  • Threshold alerting (warning/critical)
  • Prometheus export format

Phase 4: Validation 🔄 In Progress

• ✅ 4.1 JSON Data Adapter (data_adapter.py)
  • NEW: JSONEigenvalueDataAdapter class
  • Loads eigenvalue JSON files from correlation_arb512
  • Generates synthetic bars from vel_div data
  • Signal metadata extraction
  • BacktestDataLoader for high-level loading
• ⬜ 4.2 Validation Backtests (pending)
• ⬜ 4.3 Validation Analysis (pending)

---

File Structure

nautilus_dolphin/
├── nautilus_dolphin/           # Main package
│   ├── __init__.py            # Package exports
│   └── nautilus/              # Nautilus components
│       ├── __init__.py        # Component exports
│       ├── signal_bridge.py   # Redis → Nautilus bridge
│       ├── strategy.py        # Main execution strategy
│       ├── smart_exec_algorithm.py  # Entry/exit execution
│       ├── position_manager.py      # Exit management
│       ├── volatility_detector.py   # Vol regime detection
│       ├── circuit_breaker.py       # Operational safety
│       ├── metrics_monitor.py       # Stress-test metrics
│       └── data_adapter.py          # JSON backtest loader
├── tests/                     # Test suite
│   ├── test_signal_bridge.py
│   ├── test_strategy.py
│   ├── test_position_manager.py
│   ├── test_volatility_detector.py
│   ├── test_circuit_breaker.py      # NEW
│   ├── test_metrics_monitor.py      # NEW
│   └── test_smart_exec_algorithm.py # NEW
├── config/
│   └── config.yaml
├── pyproject.toml            # Package config
├── requirements.txt
└── README.md

---

New Components Detail

1. CircuitBreakerManager (circuit_breaker.py)

cb = CircuitBreakerManager(
    daily_loss_limit_pct=10.0,
    max_concurrent_positions=10,
    max_api_failures=3,
    max_order_size_pct=50.0
)

# Check before opening position
can_trade, reason = cb.can_open_position("BTCUSDT", balance)

# Track position lifecycle
cb.on_position_opened(position_id, asset)
cb.on_position_closed(position_id, asset, pnl)

# Check order size
can_submit, reason = cb.can_submit_order(notional, balance)

# Monitor API health
cb.on_api_failure(error_message)

# Manual control
cb.manual_trip("Emergency stop")
cb.reset()

# Get status
status = cb.get_status()

2. MetricsMonitor (metrics_monitor.py)

monitor = MetricsMonitor(
    config=ThresholdConfig(
        min_maker_fill_rate=48.0,
        max_slippage_bps=5.0
    )
)

# Record fills
monitor.record_fill('maker', slippage_bps=2.5)
monitor.record_fill('taker', slippage_bps=4.0)

# Record trade results
monitor.record_trade_result(pnl=100.0)

# Get metrics
summary = monitor.get_metrics_summary()
# Returns: maker_fill_rate_pct, avg_slippage_bps, 
#          win_rate_pct, profit_factor, etc.

# Prometheus export
prometheus_metrics = monitor.get_prometheus_metrics()

3. SmartExecAlgorithm Enhancements

Abort Logic (Task 3.1.5):

• Monitors quote ticks for pending entries
• Cancels order if price moves 5bps against position
• Tracks aborted entries in metrics

Fee/Slippage Tracking (Task 3.3):

• Calculates fees: 0.02% maker, 0.05% taker
• Tracks slippage: |actual - expected| / expected
• Provides metrics via get_metrics() method

4. JSONEigenvalueDataAdapter (data_adapter.py)

adapter = JSONEigenvalueDataAdapter(
    eigenvalues_dir="path/to/correlation_arb512/eigenvalues",
    venue="BINANCE_FUTURES"
)

# Load date range
adapter.load_date_range(
    start_date=datetime(2026, 2, 6),
    end_date=datetime(2026, 2, 14)
)

# Iterate through scans
for bars, signals in adapter:
    # bars: List[Bar] - synthetic OHLCV
    # signals: List[dict] - signal metadata
    process_bars(bars)
    process_signals(signals)

# Or use high-level loader
loader = BacktestDataLoader(eigenvalues_dir, venue)
data = loader.load_period(start_date, end_date, assets=['BTCUSDT', 'ETHUSDT'])

---

Strategy Integration

The DolphinExecutionStrategy now integrates all components:

class DolphinExecutionStrategy(Strategy):
    def __init__(self, config):
        # Components
        self.volatility_detector = VolatilityRegimeDetector(...)
        self.position_manager = PositionManager(...)
        self.circuit_breaker = CircuitBreakerManager(...)
        self.metrics_monitor = MetricsMonitor(...)
        
    def on_signal(self, signal):
        # 1. Apply filters
        rejection = self._should_trade(signal)
        if rejection:
            return
            
        # 2. Check circuit breaker
        can_trade, reason = self.circuit_breaker.can_open_position(...)
        if not can_trade:
            return
            
        # 3. Execute trade
        self._execute_entry(signal)
        
    def _execute_entry(self, signal):
        # Calculate size
        notional = self.calculate_position_size(signal, balance)
        
        # Check order sanity
        can_submit, reason = self.circuit_breaker.can_submit_order(...)
        
        # Submit via SmartExecAlgorithm
        self.submit_order(order, exec_algorithm_id="SMART_EXEC")

---

Test Coverage

New tests added:

1. test_circuit_breaker.py (11 tests)

   • Position limit checks
   • Daily loss limit
   • Order size sanity
   • API failure tracking
   • Manual trip/reset
   • Auto-reset after timeout

2. test_metrics_monitor.py (13 tests)

   • Fill rate calculation
   • Slippage tracking
   • Trade result recording
   • Win rate / profit factor
   • Alert generation
   • Deduplication
   • Prometheus export

3. test_smart_exec_algorithm.py (10 tests)

   • Abort logic (price movement)
   • Fee calculation (maker/taker)
   • Slippage calculation
   • Metrics tracking
   • Category classification

---

Next Steps

To complete Phase 4 (Validation):

1. Set up validation backtests:

   # Load data for validation periods
   loader = BacktestDataLoader(eigenvalues_dir)
   
   # High volatility: Feb 6-14, 2026
   feb_data = loader.load_period(
       datetime(2026, 2, 6),
       datetime(2026, 2, 14)
   )
   
   # Low volatility: Jan 21-28, 2026
   jan_data = loader.load_period(
       datetime(2026, 1, 21),
       datetime(2026, 1, 28)
   )
   

2. Run Nautilus backtests using the loaded data

3. Compare results to VBT baseline:

   • Total trades (±2% tolerance)
   • Win rate (±1% tolerance)
   • Profit factor (±3% tolerance)
   • Final capital (±5% tolerance)

---

Configuration Example

# config/config.yaml
strategy:
  venue: "BINANCE_FUTURES"
  
  # Filters
  irp_alignment_min: 0.45
  momentum_magnitude_min: 0.000075
  excluded_assets: ["TUSDUSDT", "USDCUSDT"]
  
  # Sizing
  min_leverage: 0.5
  max_leverage: 5.0
  leverage_convexity: 3.0
  capital_fraction: 0.20
  
  # Exit
  tp_bps: 99
  max_hold_bars: 120
  
  # Limits
  max_concurrent_positions: 10
  
circuit_breaker:
  daily_loss_limit_pct: 10.0
  max_api_failures: 3
  max_order_size_pct: 50.0
  auto_reset_hours: 24.0

smart_exec:
  entry_timeout_sec: 25
  entry_abort_threshold_bps: 5.0
  exit_timeout_sec: 10
  maker_fee_rate: 0.0002
  taker_fee_rate: 0.0005

metrics:
  min_maker_fill_rate: 48.0
  max_slippage_bps: 5.0
  warning_maker_fill_rate: 55.0
  critical_maker_fill_rate: 48.0

---

Running Tests

# Activate environment
activate_siloqy.bat

# Install in dev mode
pip install -e .

# Run all tests
python -m pytest tests/ -v

# Run specific test file
python -m pytest tests/test_circuit_breaker.py -v

# Run with coverage
python -m pytest tests/ --cov=nautilus_dolphin --cov-report=html

---

Notes

1. NautilusTrader dependency: The implementation requires NautilusTrader 1.200.0+ which should be installed in the siloqy environment.

2. Import errors in test: Tests will fail to import if nautilus_trader is not installed. This is expected in environments without the trading dependencies.

3. Data adapter: The JSONEigenvalueDataAdapter generates synthetic prices based on vel_div. For production backtests, consider using actual price data from Binance.

4. Redis: SignalBridgeActor requires Redis 7.0+ for the Redis Streams functionality.