trading_bot_v4/SIGNAL_QUALITY_SETUP_GUIDE.md

# Signal Quality Scoring System - Setup Guide

## Overview

The signal quality scoring system evaluates every trade signal based on 5 market context metrics before execution. Signals scoring below 91/100 are automatically blocked. This prevents overtrading and filters out low-quality setups.

**Threshold History:**
- Nov 21 morning: Raised to 81 after v8 initial success (94.2 avg quality, 66.7% WR)
- Nov 21 evening: Raised to 91 after trade #7 loss (ADX 19.0, quality 90, -$387)

**Data Validation (7 v8 trades):**
Perfect quality score separation validates 91 threshold:
- **ALL 4 winners:** Quality ≥95 (scores: 95, 95, 100, 105) ✅
- **ALL 3 losers:** Quality ≤90 (scores: 80, 90, 90) ❌
- **Conclusion:** 91 threshold would have prevented 100% of losses (-$624.90 total)

## ✅ Completed Components

### 1. TradingView Indicator ✅
- **File:** `workflows/trading/moneyline_v5_final.pinescript`
- **Status:** Complete and tested
- **Metrics sent:** ATR%, ADX, RSI, Volume Ratio, Price Position
- **Alert format:** `SOL buy .P 15 | ATR:1.85 | ADX:28.3 | RSI:62.5 | VOL:1.45 | POS:75.3`

### 2. n8n Parse Signal Enhanced ✅
- **File:** `workflows/trading/parse_signal_enhanced.json`
- **Status:** Complete and tested
- **Function:** Extracts 5 context metrics from alert messages
- **Backward compatible:** Works with old format (metrics default to 0)

### 3. Trading Bot API ✅
- **check-risk endpoint:** Scores signals 0-100, blocks if <60
- **execute endpoint:** Stores context metrics in database
- **Database schema:** Updated with 5 new fields
- **Status:** Built, deployed, running

## 📋 n8n Workflow Update Instructions

### Step 1: Import Parse Signal Enhanced Node

1. Open n8n workflow editor
2. Go to "Money Machine" workflow
3. Click the "+" icon to add a new node
4. Select "Code" → "Import from file"
5. Import: `/home/icke/traderv4/workflows/trading/parse_signal_enhanced.json`

### Step 2: Replace Old Parse Signal Node

**Old Node (lines 23-52 in Money_Machine.json):**
```json
{
  "parameters": {
    "fields": {
      "values": [
        {
          "name": "rawMessage",
          "stringValue": "={{ $json.body }}"
        },
        {
          "name": "symbol",
          "stringValue": "={{ $json.body.match(/\\bSOL\\b/i) ? 'SOL-PERP' : ... }}"
        },
        {
          "name": "direction",
          "stringValue": "={{ $json.body.match(/\\b(sell|short)\\b/i) ? 'short' : 'long' }}"
        },
        {
          "name": "timeframe",
          "stringValue": "={{ $json.body.match(/\\.P\\s+(\\d+)/)?.[1] || '15' }}"
        }
      ]
    }
  },
  "name": "Parse Signal",
  "type": "n8n-nodes-base.set"
}
```

**New Node (Parse Signal Enhanced):**
- Extracts: symbol, direction, timeframe (same as before)
- NEW: Also extracts ATR, ADX, RSI, volumeRatio, pricePosition
- Place after the "Webhook" node
- Connect: Webhook → Parse Signal Enhanced → 15min Chart Only?

### Step 3: Update Check Risk Node

**Current jsonBody (line 103):**
```json
{
  "symbol": "{{ $json.symbol }}",
  "direction": "{{ $json.direction }}"
}
```

**Updated jsonBody (add 5 context metrics):**
```json
{
  "symbol": "{{ $json.symbol }}",
  "direction": "{{ $json.direction }}",
  "atr": {{ $json.atr || 0 }},
  "adx": {{ $json.adx || 0 }},
  "rsi": {{ $json.rsi || 0 }},
  "volumeRatio": {{ $json.volumeRatio || 0 }},
  "pricePosition": {{ $json.pricePosition || 0 }}
}
```

### Step 4: Update Execute Trade Node

**Current jsonBody (line 157):**
```json
{
  "symbol": "{{ $('Parse Signal').item.json.symbol }}",
  "direction": "{{ $('Parse Signal').item.json.direction }}",
  "timeframe": "{{ $('Parse Signal').item.json.timeframe }}",
  "signalStrength": "strong"
}
```

**Updated jsonBody (add 5 context metrics):**
```json
{
  "symbol": "{{ $('Parse Signal Enhanced').item.json.symbol }}",
  "direction": "{{ $('Parse Signal Enhanced').item.json.direction }}",
  "timeframe": "{{ $('Parse Signal Enhanced').item.json.timeframe }}",
  "signalStrength": "strong",
  "atr": {{ $('Parse Signal Enhanced').item.json.atr || 0 }},
  "adx": {{ $('Parse Signal Enhanced').item.json.adx || 0 }},
  "rsi": {{ $('Parse Signal Enhanced').item.json.rsi || 0 }},
  "volumeRatio": {{ $('Parse Signal Enhanced').item.json.volumeRatio || 0 }},
  "pricePosition": {{ $('Parse Signal Enhanced').item.json.pricePosition || 0 }}
}
```

### Step 5: Update Telegram Notification (Optional)

You can add quality score to Telegram messages:

**Current message template (line 200):**
```
🟢 TRADE OPENED

📊 Symbol: ${symbol}
📈 Direction: ${direction}
...
```

**Enhanced message template:**
```
🟢 TRADE OPENED

📊 Symbol: ${symbol}
📈 Direction: ${direction}
🎯 Quality Score: ${$('Check Risk').item.json.qualityScore || 'N/A'}/100
...
```

## 🧪 Testing Instructions

### Test 1: High-Quality Signal (Should Execute)

Send webhook:
```bash
curl -X POST http://localhost:5678/webhook/tradingview-bot-v4 \
  -H "Content-Type: application/json" \
  -d '{"body": "SOL buy .P 15 | ATR:1.85 | ADX:32.3 | RSI:58.5 | VOL:1.65 | POS:45.3"}'
```

**Expected:**
- Parse Signal Enhanced extracts all 5 metrics
- Check Risk calculates quality score ~80/100
- Check Risk returns `passed: true`
- Execute Trade runs and stores metrics in database
- Telegram notification sent

### Test 2: Low-Quality Signal (Should Block)

Send webhook:
```bash
curl -X POST http://localhost:5678/webhook/tradingview-bot-v4 \
  -H "Content-Type: application/json" \
  -d '{"body": "SOL buy .P 15 | ATR:0.35 | ADX:12.8 | RSI:78.5 | VOL:0.45 | POS:92.1"}'
```

**Expected:**
- Parse Signal Enhanced extracts all 5 metrics
- Check Risk calculates quality score ~20/100
- Check Risk returns `passed: false, reason: "Signal quality too low (20/100). Issues: ATR too low (chop/low volatility), Weak/no trend (ADX), RSI extreme vs direction, Volume too low, Chasing (long near range top)"`
- Execute Trade does NOT run
- Telegram error notification sent

### Test 3: Backward Compatibility (Should Execute)

Send old format without metrics:
```bash
curl -X POST http://localhost:5678/webhook/tradingview-bot-v4 \
  -H "Content-Type: application/json" \
  -d '{"body": "SOL buy .P 15"}'
```

**Expected:**
- Parse Signal Enhanced extracts symbol/direction/timeframe, metrics default to 0
- Check Risk skips quality scoring (ATR=0 means no metrics)
- Check Risk returns `passed: true` (only checks risk limits)
- Execute Trade runs with null metrics
- Backward compatible

## 📊 Scoring Logic

### Scoring Breakdown (Base: 50 points)

1. **ATR Check** (-15 to +10 points)
   - ATR < 0.6%: -15 (choppy/low volatility)
   - ATR > 2.5%: -20 (extreme volatility)
   - 0.6-2.5%: +10 (healthy)

2. **ADX Check** (-15 to +15 points)
   - ADX > 25: +15 (strong trend)
   - ADX 18-25: +5 (moderate trend)
   - ADX < 18: -15 (weak/no trend)

3. **RSI Check** (-10 to +10 points)
   - Long + RSI > 50: +10 (momentum supports)
   - Long + RSI < 30: -10 (extreme oversold)
   - Short + RSI < 50: +10 (momentum supports)
   - Short + RSI > 70: -10 (extreme overbought)

4. **Volume Check** (-10 to +10 points)
   - Volume > 1.2x avg: +10 (strong participation)
   - Volume < 0.8x avg: -10 (low participation)
   - 0.8-1.2x avg: 0 (neutral)

5. **Price Position Check** (-15 to +5 points)
   - Long at range top (>80%): -15 (chasing)
   - Short at range bottom (<20%): -15 (chasing)
   - Otherwise: +5 (good position)

**Minimum Passing Score:** 60/100

### Example Scores

**Perfect Setup (Score: 90):**
- ATR: 1.5% (+10)
- ADX: 32 (+15)
- RSI: 58 (long) (+10)
- Volume: 1.8x (+10)
- Price: 45% (+5)
- **Total:** 50 + 10 + 15 + 10 + 10 + 5 = 90

**Terrible Setup (Score: 20):**
- ATR: 0.3% (-15)
- ADX: 12 (-15)
- RSI: 78 (long) (-10)
- Volume: 0.5x (-10)
- Price: 92% (-15)
- **Total:** 50 - 15 - 15 - 10 - 10 - 15 = -5 → Clamped to 0

## 🔍 Monitoring

### Check Logs

Watch check-risk decisions:
```bash
docker logs trading-bot-v4 --tail 100 -f | grep "Signal quality"
```

Example output:
```
✅ Signal quality: 75/100 - HIGH QUALITY
🎯 Quality reasons: Strong trend (ADX: 32.3), Healthy volatility (ATR: 1.85%), Good volume (1.65x avg), RSI supports direction (58.5), Good entry position (45.3%)
```

```
❌ Signal quality: 35/100 - TOO LOW (minimum: 60)
⚠️  Quality reasons: Weak/no trend (ADX: 12.8), ATR too low (chop/low volatility), RSI extreme vs direction, Volume too low, Chasing (long near range top)
```

### Database Query

Check stored metrics:
```sql
SELECT 
  symbol, 
  direction, 
  entryPrice,
  atrAtEntry,
  adxAtEntry,
  rsiAtEntry,
  volumeAtEntry,
  pricePositionAtEntry,
  realizedPnL
FROM "Trade"
WHERE createdAt > NOW() - INTERVAL '7 days'
ORDER BY createdAt DESC;
```

## 🎛️ Tuning Parameters

All scoring thresholds are in `app/api/trading/check-risk/route.ts` (lines 210-320):

```typescript
// ATR thresholds
if (atr < 0.6) points -= 15  // Too low
if (atr > 2.5) points -= 20  // Too high

// ADX thresholds
if (adx > 25) points += 15   // Strong trend
if (adx < 18) points -= 15   // Weak trend

// Minimum passing score
if (score < 60) {
  return { passed: false, ... }
}
```

Adjust these based on backtesting results. For example:
- If too many good trades blocked: Lower minimum score to 50
- If still overtrading: Increase ADX threshold to 30
- For different assets: Adjust ATR ranges (crypto vs stocks)

## 📈 Next Steps

1. **Deploy to Production:**
   - Update n8n workflow (Steps 1-5 above)
   - Test with both formats
   - Monitor logs for quality decisions

2. **Collect Data:**
   - Run for 2 weeks to gather quality scores
   - Analyze correlation: quality score vs P&L
   - Identify which metrics matter most

3. **Optimize:**
   - Query database: `SELECT AVG(realizedPnL) FROM Trade WHERE adxAtEntry > 25`
   - Fine-tune thresholds based on results
   - Consider dynamic scoring (different weights per symbol/timeframe)

4. **Future Enhancements:**
   - Add more metrics (spread, funding rate, correlation)
   - Machine learning: Train on historical trades
   - Per-asset scoring models
   - Signal source scoring (TradingView vs manual)

## 🚨 Troubleshooting

**Problem:** All signals blocked
- Check logs: `docker logs trading-bot-v4 | grep "quality"`
- Likely: TradingView not sending metrics (verify alert format)
- Workaround: Temporarily lower minimum score to 40

**Problem:** No metrics in database
- Check Parse Signal Enhanced extracted metrics: View n8n execution
- Verify Check Risk received metrics: `curl localhost:3001/api/trading/check-risk` with test data
- Check execute endpoint logs: Should show "Context metrics: ATR:..."

**Problem:** Metrics always 0
- TradingView alert not using enhanced indicator
- Parse Signal Enhanced regex not matching
- Test parsing: `node -e "console.log('SOL buy .P 15 | ATR:1.85'.match(/ATR:([\d.]+)/))"` 

## 📝 Files Modified

- ✅ `workflows/trading/moneyline_v5_final.pinescript` - Enhanced indicator
- ✅ `workflows/trading/parse_signal_enhanced.json` - n8n parser
- ✅ `app/api/trading/check-risk/route.ts` - Quality scoring
- ✅ `app/api/trading/execute/route.ts` - Store metrics
- ✅ `lib/database/trades.ts` - Updated interface
- ✅ `prisma/schema.prisma` - Added 5 fields
- ✅ `prisma/migrations/...add_rsi_and_price_position_metrics/` - Migration
- ⏳ `workflows/trading/Money_Machine.json` - Manual update needed

## 🎯 Success Criteria

Signal quality scoring is working correctly when:

1. ✅ TradingView sends alerts with metrics
2. ✅ n8n Parse Signal Enhanced extracts all 5 metrics
3. ✅ Check Risk calculates quality score 0-100
4. ✅ Low-quality signals (<60) are blocked with reasons
5. ✅ High-quality signals (>60) execute normally
6. ✅ Context metrics stored in database for every trade
7. ✅ Backward compatible with old alerts (metrics=0, scoring skipped)
8. ✅ Logs show quality score and reasons for every signal

---

**Status:** Ready for production testing
**Last Updated:** 2024-10-30
**Author:** Trading Bot v4 Signal Quality System