trading_bot_v4/BLOCKED_SIGNALS_TRACKING.md

Blocked Signals Tracking System

Date Implemented: November 11, 2025
Status: ✅ ACTIVE

Overview

Automatically tracks all signals that get blocked by the trading bot's risk checks. This data allows us to analyze whether blocked signals would have been profitable, helping optimize the signal quality thresholds over time.

What Gets Tracked

Every time a signal is blocked, the system saves:

Signal Metrics

• Symbol (e.g., SOL-PERP)
• Direction (long/short)
• Timeframe (5min, 15min, 1H, etc.)
• Price at signal time
• ATR, ADX, RSI, volume ratio, price position

Quality Score

• Calculated score (0-100)
• Score version (v4 = current)
• Detailed breakdown of scoring reasons
• Minimum score required (currently 65)

Block Reason

• QUALITY_SCORE_TOO_LOW - Score below threshold
• COOLDOWN_PERIOD - Too soon after last trade
• HOURLY_TRADE_LIMIT - Too many trades in last hour
• DAILY_DRAWDOWN_LIMIT - Max daily loss reached

Future Analysis Fields (NOT YET IMPLEMENTED)

• priceAfter1Min, priceAfter5Min, priceAfter15Min, priceAfter30Min
• wouldHitTP1, wouldHitTP2, wouldHitSL
• analysisComplete

These will be filled by a monitoring job that tracks what happened after each blocked signal.

Database Table

Table: BlockedSignal
- id (PK)
- createdAt (timestamp)
- symbol, direction, timeframe
- signalPrice, atr, adx, rsi, volumeRatio, pricePosition
- signalQualityScore, signalQualityVersion, scoreBreakdown (JSON)
- minScoreRequired, blockReason, blockDetails
- priceAfter1Min/5Min/15Min/30Min (for future analysis)
- wouldHitTP1/TP2/SL, analysisComplete

Query Examples

Recent Blocked Signals

SELECT 
  symbol, 
  direction,
  signalQualityScore as score,
  minScoreRequired as threshold,
  blockReason,
  createdAt
FROM "BlockedSignal"
ORDER BY createdAt DESC
LIMIT 20;

Blocked by Quality Score (60-64 range)

SELECT 
  symbol,
  direction,
  signalQualityScore,
  ROUND(atr::numeric, 2) as atr,
  ROUND(adx::numeric, 1) as adx,
  ROUND(rsi::numeric, 1) as rsi,
  ROUND(pricePosition::numeric, 1) as pos,
  blockDetails
FROM "BlockedSignal"
WHERE blockReason = 'QUALITY_SCORE_TOO_LOW'
  AND signalQualityScore >= 60
  AND signalQualityScore < 65
ORDER BY createdAt DESC;

Breakdown by Block Reason

SELECT 
  blockReason,
  COUNT(*) as count,
  ROUND(AVG(signalQualityScore)::numeric, 1) as avg_score,
  MIN(signalQualityScore) as min_score,
  MAX(signalQualityScore) as max_score
FROM "BlockedSignal"
GROUP BY blockReason
ORDER BY count DESC;

Today's Blocked Signals

SELECT 
  TO_CHAR(createdAt, 'HH24:MI:SS') as time,
  symbol,
  direction,
  signalQualityScore,
  blockReason
FROM "BlockedSignal"
WHERE createdAt >= CURRENT_DATE
ORDER BY createdAt DESC;

Analysis Workflow

Step 1: Collect Data (Current Phase)

• Bot automatically saves blocked signals
• Wait for 10-20 blocked signals to accumulate
• No action needed - runs automatically

Step 2: Manual Analysis (When Ready)

-- Check how many blocked signals we have
SELECT COUNT(*) FROM "BlockedSignal";

-- Analyze score distribution
SELECT 
  CASE 
    WHEN signalQualityScore >= 60 THEN '60-64 (Close Call)'
    WHEN signalQualityScore >= 55 THEN '55-59 (Marginal)'
    WHEN signalQualityScore >= 50 THEN '50-54 (Weak)'
    ELSE '0-49 (Very Weak)'
  END as score_tier,
  COUNT(*) as count,
  ROUND(AVG(atr)::numeric, 2) as avg_atr,
  ROUND(AVG(adx)::numeric, 1) as avg_adx
FROM "BlockedSignal"
WHERE blockReason = 'QUALITY_SCORE_TOO_LOW'
GROUP BY score_tier
ORDER BY MIN(signalQualityScore) DESC;

Step 3: Future Automation (Not Yet Built)

Create a monitoring job that:

1. Fetches BlockedSignal records where analysisComplete = false and createdAt > 30min ago
2. Gets price history for those timestamps
3. Calculates if TP1/TP2/SL would have been hit
4. Updates the record with analysis results
5. Sets analysisComplete = true

Integration Points

Code Files Modified

1. prisma/schema.prisma - Added BlockedSignal model
2. lib/database/trades.ts - Added createBlockedSignal() function
3. app/api/trading/check-risk/route.ts - Saves blocked signals

Where Blocking Happens

• Quality score check (line ~311-350)
• Cooldown period check (line ~281-303)
• Hourly trade limit (line ~235-258)
• Daily drawdown limit (line ~211-223)

Next Steps

Phase 1: Data Collection (CURRENT)

• ✅ Database table created
• ✅ Automatic saving implemented
• ✅ Bot deployed and running
• ⏳ Collect 10-20 blocked signals (wait ~1-2 weeks)

Phase 2: Analysis

• Query blocked signal patterns
• Identify "close calls" (score 60-64)
• Compare with executed trades that had similar scores
• Determine if threshold adjustment is warranted

Phase 3: Automation (Future)

• Build price monitoring job
• Auto-calculate would-be outcomes
• Generate reports on missed opportunities
• Feed data into threshold optimization algorithm

Benefits

1. Data-Driven Decisions - No guessing, only facts
2. Prevents Over-Optimization - Wait for statistically significant sample
3. Tracks All Block Reasons - Not just quality score
4. Historical Record - Can review past decisions
5. Continuous Improvement - System learns from what it blocks

Important Notes

⚠️ Don't change thresholds prematurely!

• 2 trades is NOT enough data
• Wait for 10-20 blocked signals minimum
• Analyze patterns before making changes

✅ System is working correctly if:

• Blocked signals appear in database
• Each has metrics (ATR, ADX, RSI, etc.)
• Block reason is recorded
• Timestamp is correct

❌ Troubleshooting:

• If no blocked signals appear: Check bot is receiving TradingView alerts with metrics
• If missing metrics: Ensure TradingView webhook includes ATR/ADX/RSI/volume/pricePosition
• If database errors: Check Prisma client is regenerated after schema changes

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Last Updated: November 11, 2025
Version: 1.0
Maintained By: Trading Bot v4 Development Team