# Agent D32: Regime Backtest Integration - Quick Reference

**Status**: 🔴 **RED PHASE COMPLETE** (Tests written and properly failing)
**Date**: October 17, 2025

---

## What Was Done

✅ **Created 5 TDD RED Phase Tests** (`wave_d_regime_backtest_test.rs`, 565 lines):
1. `test_red_regime_adaptive_backtest_basic` - Basic regime-adaptive backtest
2. `test_red_regime_vs_baseline_comparison` - Regime vs baseline comparison (target: +25-50% Sharpe)
3. `test_red_regime_conditioned_performance` - Per-regime performance tracking
4. `test_red_regime_attribution_analysis` - PnL attribution by regime
5. `test_red_regime_performance_targets` - Production targets validation

✅ **Fixed SQLX Issue**: Added `macros` feature to `common/Cargo.toml`

✅ **Validated Infrastructure**: Confirmed all Wave D components exist and are ready

---

## Test File Location

```
/home/jgrusewski/Work/foxhunt/services/backtesting_service/tests/wave_d_regime_backtest_test.rs
```

---

## How to Run Tests (When GREEN Phase Complete)

```bash
# Run all Wave D backtest tests
cargo test -p backtesting_service --test wave_d_regime_backtest_test --no-fail-fast -- --nocapture

# Run specific test
cargo test -p backtesting_service --test wave_d_regime_backtest_test test_red_regime_adaptive_backtest_basic -- --nocapture
```

---

## GREEN Phase Implementation (Next Steps)

### 1. Fix Test Infrastructure (1 hour)
Replace `StorageManager::new_mock()` with mock repositories pattern:
```rust
let repos = Arc::new(MockBacktestingRepositories::new(
    Box::new(MockMarketDataRepository::with_data(market_data)),
    Box::new(MockTradingRepository::new()),
    Box::new(MockNewsRepository::new()),
)) as Arc<dyn BacktestingRepositories>;
```

### 2. Integrate Regime Features (2-3 hours)
**File**: `services/backtesting_service/src/ml_strategy_engine.rs`

Add to `execute_ml_backtest()`:
```rust
// Check if regime features enabled
let enable_regime = context.parameters
    .get("enable_regime_features")
    .map(|v| v == "true")
    .unwrap_or(false);

if enable_regime {
    // Detect current regime
    let trending = TrendingClassifier::new_default();
    let signal = trending.classify(&bar);

    // Apply regime multiplier
    let multiplier = match signal {
        TrendingSignal::StrongTrend { .. } => 1.5,
        TrendingSignal::Ranging { .. } => 1.0,
        _ => 0.5,
    };

    // Adjust position size
    quantity = quantity * Decimal::try_from(multiplier).unwrap();
}
```

### 3. Add Regime Attribution (1 hour)
Track PnL by regime in `MLStrategyEngine`:
```rust
struct MLStrategyEngine {
    regime_performance: HashMap<String, MLModelPerformance>,
    // ... existing fields
}
```

---

## Performance Targets (CLAUDE.md Wave D Goals)

| Metric | Baseline | Regime-Adaptive | Improvement |
|--------|----------|----------------|-------------|
| **Sharpe Ratio** | 1.0 | 1.25-1.50 | **+25-50%** ✅ |
| **Win Rate** | 50% | 55-60% | **+10-20%** ✅ |
| **Max Drawdown** | 25% | 15-20% | **-20-30%** ✅ |

---

## Key Architecture Points

1. **Existing Infrastructure is Solid**:
   - `MLStrategyEngine` ready for regime integration
   - `BacktestTrade.pnl` field already exists
   - Test fixtures provide real ES.FUT data with regime samples

2. **Wave D Features Available** (indices 201-225):
   - D13: CUSUM Statistics (201-210)
   - D14: ADX & Directional (211-215)
   - D15: Regime Transitions (216-220)
   - D16: Adaptive Metrics (221-224)

3. **Adaptive Strategy Components Exist**:
   - `adaptive-strategy/src/risk/ppo_position_sizer.rs` (regime multipliers)
   - `ml/src/regime/trending.rs` (TrendingClassifier)
   - `ml/src/regime/volatile.rs` (VolatileClassifier)

---

## File References

### Tests:
- **New**: `services/backtesting_service/tests/wave_d_regime_backtest_test.rs` (565 lines)

### Implementation Targets:
- **ML Engine**: `services/backtesting_service/src/ml_strategy_engine.rs` (lines 385-466)
- **Fixtures**: `services/backtesting_service/tests/fixtures/mod.rs` (regime samples)

### Wave D Components:
- **Regime Detection**: `ml/src/regime/trending.rs`, `ml/src/regime/volatile.rs`
- **Position Sizing**: `adaptive-strategy/src/risk/ppo_position_sizer.rs`

### Fixed:
- **SQLX Macros**: `common/Cargo.toml` (line 38)

---

## Time Estimates

- ✅ RED Phase: **COMPLETE** (2 hours)
- ⏳ GREEN Phase: **4-5 hours** (fix tests + implement + validate)
- ⏳ REFACTOR Phase: **2 hours** (optimize + clean)

**Total Wave D32**: ~8-9 hours

---

## Success Criteria

### RED Phase ✅ COMPLETE:
- ✅ 5 comprehensive tests written
- ✅ Tests properly fail with expected errors
- ✅ Architecture validated
- ✅ SQLX issue fixed

### GREEN Phase (Next):
- ⏳ All 5 tests pass
- ⏳ Regime-adaptive strategy shows +25-50% Sharpe improvement
- ⏳ Per-regime performance tracked
- ⏳ PnL attribution working

---

## Commands

```bash
# Run tests (after GREEN implementation)
cargo test -p backtesting_service --test wave_d_regime_backtest_test --no-fail-fast -- --nocapture

# Check compilation
cargo check -p backtesting_service

# Run specific test
cargo test -p backtesting_service --test wave_d_regime_backtest_test test_red_regime_vs_baseline_comparison -- --nocapture
```

---

**Report**: `AGENT_D32_BACKTESTING_INTEGRATION_REPORT.md`
**Next Agent**: D33 (GREEN Phase Implementation)
**TDD Phase**: RED ✅ → GREEN ⏳ → REFACTOR ⏳