6.4 KiB
Phase 1 Implementation Summary
✅ Completed Features
1. Price Reaction Tracking
File: backend/python_service/services/price_reaction_tracker.py
What it does:
- Tracks price movement 5, 15, and 30 minutes after a signal appears
- Calculates price reaction percentages
- Detects high/low breaks
- Flags if flow led to actual price movement (filters hedges/rolls)
New Fields Added:
price_reaction_5m_pct- Price change 5 minutes after signal (%)price_reaction_15m_pct- Price change 15 minutes after signal (%)price_reaction_30m_pct- Price change 30 minutes after signal (%)high_break_5m- Boolean: did price break high within 5m?low_break_5m- Boolean: did price break low within 5m?flow_led_to_move- Boolean: did flow lead to >0.5% price move?
Integration: Called in main.py after price enrichment
2. VWAP Integration
File: backend/python_service/services/price_context.py (extended)
What it does:
- Calculates VWAP (Volume Weighted Average Price) for each trading day
- VWAP = SUM(price * volume) / SUM(volume) from RTH open (9:30 AM) to signal time
- Calculates distance from VWAP for entry/exit logic
New Fields Added:
vwap_at_signal- VWAP value at signal timeprice_vs_vwap_pct- Percentage distance from VWAP
Integration: Integrated into enrich_flow_with_prices() method
Usage:
- Entry: VWAP pullback or VWAP reclaim
- Exit: Price rejection of VWAP
- Filter: Price too extended from VWAP (>2%) = wait for pullback
3. Signal Tier Classification
File: backend/python_service/services/signal_tier_classifier.py
What it does:
- Classifies signals into Tier-1, Tier-2, or Ignore
- Tier-1: 🟢/🔴 + 💎 + ⭐ + premium > 500K + direction aligned (tradeable alone)
- Tier-2: 🟢 + 💎 (no ⭐) OR ⭐ without 💎 (needs confirmation)
- Ignore: OTM-only, mixed signals, low volume/OI ratio
New Fields Added:
signal_tier- 'TIER_1', 'TIER_2', or 'IGNORE'is_tradeable- Boolean: True for Tier-1 only
Integration: Called in main.py after rocket score calculation
Filtering Logic:
- OTM-only prints → Ignore
- Mixed 🟢/🔴 with no net premium edge → Ignore
- Big premium but volume << OI (likely rolls/hedges) → Ignore
4. Trade Checklist
File: backend/python_service/services/trade_checklist.py
What it does:
- Evaluates signals against 5-point checklist
- Requires 4/5 checks to pass
- Prevents bad trades
Checklist Items:
- ✅ Has direction (🟢 or 🔴)
- ✅ Has diamond (💎)
- ✅ Has star (⭐)
- ✅ Price respects VWAP (within ±2%, or ±1% for direction)
- ✅ Index confirms (placeholder - will be added in Phase 2)
New Fields Added:
checklist_score- Score out of 5 (0-5)checklist_passed- Boolean: True if score >= 4checklist_details- Dict with individual check results
Integration: Called in main.py after price reaction tracking
Usage:
- Only trade signals with
checklist_passed = True - Review
checklist_detailsto see which checks passed/failed
📊 Data Flow
Raw Options Flow
↓
OptionsFlowProcessor.process()
↓
PriceContextService.enrich_flow_with_prices() [VWAP added here]
↓
AlertService.match_alerts_to_flows()
↓
OptionsFlowProcessor.process_rocket_score()
↓
SignalTierClassifier.classify_tiers() [NEW]
↓
PriceReactionTracker.enrich_with_reactions() [NEW]
↓
TradeChecklist.evaluate_all() [NEW]
↓
OutputFormatter.format_final_output()
↓
API Response
🔍 New API Response Fields
All new fields are automatically included in the API response. Key fields to use:
For Filtering:
signal_tier- Filter to 'TIER_1' for best signalsis_tradeable- Boolean flag for tradeable signalschecklist_passed- Boolean flag for checklist-passed signalsflow_led_to_move- Boolean flag for signals that moved price
For Entry/Exit:
vwap_at_signal- VWAP value for entry logicprice_vs_vwap_pct- Distance from VWAPprice_reaction_5m_pct- Price reaction after signal
For Analysis:
checklist_score- Checklist score (0-5)checklist_details- Detailed check results (JSON)
🎯 Usage Examples
Filter to Tier-1 Signals Only:
# In your frontend or API consumer:
filtered = [row for row in data if row.get('signal_tier') == 'TIER_1']
Filter to Checklist-Passed Signals:
filtered = [row for row in data if row.get('checklist_passed') == True]
Filter to Signals That Led to Price Moves:
filtered = [row for row in data if row.get('flow_led_to_move') == True]
Combined Filter (Best Signals):
best_signals = [
row for row in data
if row.get('signal_tier') == 'TIER_1'
and row.get('checklist_passed') == True
and row.get('flow_led_to_move') == True
]
🚀 Next Steps
Immediate:
- Test the API endpoint to see new fields in response
- Update frontend to display new fields
- Add filters for Tier-1 and checklist-passed signals
Phase 2 (Next):
- Strike clustering detection
- Delta weighting
- Index correlation (SPY/QQQ/VIX)
📝 Notes
- All new services follow existing code patterns
- No breaking changes to existing functionality
- New fields are optional (won't break if missing)
- Price reaction tracking may be slower for large datasets (batched queries)
- VWAP calculation only works during RTH (9:30 AM - 4:00 PM)
🐛 Known Limitations
-
Price Reaction Tracking:
- Only tracks if price data exists at 5m/15m/30m intervals
- May be None for signals near market close
- Uses 0.5% threshold for "flow led to move" (configurable)
-
VWAP Calculation:
- Only calculated during RTH (9:30 AM - 4:00 PM)
- Returns None for PRE/POST market signals
- Requires 1-minute bar data
-
Index Correlation:
- Currently returns False (placeholder)
- Will be implemented in Phase 2
-
Checklist:
- Index confirmation check always fails (Phase 2)
- VWAP check may fail if VWAP not available (PRE/POST market)
✅ Testing Checklist
- API returns new fields in response
- Tier classification works correctly
- Price reaction tracking populates correctly
- VWAP calculation works during RTH
- Checklist evaluation works correctly
- No errors in logs
- Performance is acceptable
Implementation Date: Phase 1 Complete Status: ✅ Ready for Testing