# 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`)

```python
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`)

```python
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`)

```python
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:

```python
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**:
   ```python
   # 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

```yaml
# 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

```bash
# 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.