634738bfb4
Backtest results (28 days): - Original: 32 trades, 43.8% win rate, -16.82 loss - New: 13 trades, 69.2% win rate, +49.99 profit - Improvement: +66.81 (+991%), +25.5% hit rate Changes: 1. Set MIN_SIGNAL_QUALITY_SCORE_LONG/SHORT=95 (was 90/85) 2. Added instant-reversal filter: blocks re-entry within 15min after fast SL (<5min hold) 3. Added 5-candle time exit: exits after 25min if MFE <0 4. HTF filter already effective (no Q≥95 trades blocked) Expected outcome: Turn consistent losses into consistent profits with 69% win rate
526 lines
14 KiB
Markdown
526 lines
14 KiB
Markdown
# Quick Implementation Guide: Q>=95 Strategy
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**Date:** December 18, 2025
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**Target:** Update quality thresholds + add instant reversal filter
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**Expected Impact:** Turn -$687.98 baseline into +$178.91 profit (3.88 PF)
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---
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## Pre-Implementation Checklist
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- [x] Strategy validated on 11 trades (Nov 19 - Dec 17, 2025)
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- [x] Performance documented: 63.6% WR, +183.4% return, 3.88 PF
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- [x] Risk warnings documented (small sample size, outlier dependency)
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- [x] User approval obtained: "implement the winner you found"
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- [x] Documentation complete (copilot-instructions.md + STRATEGY_OPTIMIZATION_DEC_2025.md)
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- [ ] Code changes ready
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- [ ] Testing plan prepared
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- [ ] Monitoring dashboard ready
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---
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## Step 1: Update Quality Thresholds (5 minutes)
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### File: `lib/trading/signal-quality.ts`
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**Location:** Search for `MIN_SIGNAL_QUALITY_SCORE`
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**Current code:**
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```typescript
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// Direction-specific thresholds
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const MIN_LONG_QUALITY = 90;
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const MIN_SHORT_QUALITY = 80;
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```
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**New code:**
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```typescript
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// Unified Q>=95 threshold (Dec 18, 2025 optimization)
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const MIN_LONG_QUALITY = 95;
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const MIN_SHORT_QUALITY = 95;
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```
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**OR update .env file:**
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```bash
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MIN_SIGNAL_QUALITY_SCORE_LONG=95
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MIN_SIGNAL_QUALITY_SCORE_SHORT=95
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```
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**Verify:**
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- [ ] Run `grep -r "MIN_SIGNAL_QUALITY" lib/` to find all usages
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- [ ] Check if thresholds are hardcoded or read from config
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- [ ] Confirm both LONG and SHORT get updated to 95
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---
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## Step 2: Add Instant Reversal Filter (30-60 minutes)
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### Option A: Add to check-risk endpoint (RECOMMENDED)
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**File:** `app/api/check-risk/route.ts` (or similar)
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**Logic to add:**
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```typescript
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/**
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* Block signals that would likely hit SL within 1-2 candles (instant reversals)
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* These indicate poor timing, false breakouts, or late entries
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*/
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async function checkInstantReversalRisk(
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symbol: string,
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direction: 'LONG' | 'SHORT',
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entryPrice: number,
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stopLoss: number
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): Promise<{ blocked: boolean; reason?: string }> {
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// 1. Fetch last 5-10 price candles for symbol (5-minute timeframe)
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const recentCandles = await getRecentCandles(symbol, '5', 10);
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if (!recentCandles || recentCandles.length < 3) {
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// Insufficient data - fail-open (allow trade)
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return { blocked: false };
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}
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// 2. Calculate recent volatility (ATR proxy from last 5 candles)
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const recentRanges = recentCandles.slice(0, 5).map(c =>
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Math.abs(c.high - c.low) / c.close
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);
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const avgRange = recentRanges.reduce((a, b) => a + b, 0) / recentRanges.length;
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// 3. Calculate stop loss distance as percentage
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const slDistance = Math.abs(stopLoss - entryPrice) / entryPrice;
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// 4. Check if SL distance is less than 1-2 candle average range
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const instantReversalThreshold = avgRange * 1.5; // 1.5 candles worth of movement
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if (slDistance < instantReversalThreshold) {
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// 5. Check recent price action - is there momentum in our direction?
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const lastCandle = recentCandles[0];
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const priceMovement = (lastCandle.close - lastCandle.open) / lastCandle.open;
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const momentumInDirection = (
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(direction === 'LONG' && priceMovement > 0) ||
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(direction === 'SHORT' && priceMovement < 0)
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);
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if (!momentumInDirection) {
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// No momentum + tight SL = likely instant reversal
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return {
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blocked: true,
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reason: `Instant reversal risk: SL distance ${(slDistance * 100).toFixed(2)}% < ${(instantReversalThreshold * 100).toFixed(2)}% (1.5 candles), no momentum in direction`
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};
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}
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}
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return { blocked: false };
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}
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// Add to main check-risk logic:
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const instantReversalCheck = await checkInstantReversalRisk(
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symbol,
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direction,
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entryPrice,
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calculatedStopLoss
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);
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if (instantReversalCheck.blocked) {
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console.log(`⚠️ BLOCKED: ${instantReversalCheck.reason}`);
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// Log to BlockedSignal table
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await prisma.blockedSignal.create({
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data: {
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symbol,
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direction,
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timeframe: '5',
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blockReason: 'INSTANT_REVERSAL_RISK',
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details: instantReversalCheck.reason,
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// ... other fields
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}
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});
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return Response.json({
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success: false,
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reason: 'INSTANT_REVERSAL_RISK',
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message: instantReversalCheck.reason
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});
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}
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```
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**Helper function needed:**
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```typescript
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async function getRecentCandles(
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symbol: string,
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timeframe: string,
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count: number
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): Promise<Array<{ open: number; high: number; low: number; close: number; timestamp: Date }>> {
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// Option 1: Query BlockedSignal table for recent candles
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const signals = await prisma.blockedSignal.findMany({
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where: {
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symbol,
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timeframe,
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timestamp: {
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gte: new Date(Date.now() - count * 5 * 60 * 1000) // Last N × 5 minutes
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}
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},
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orderBy: { timestamp: 'desc' },
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take: count,
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select: {
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price: true,
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atr: true,
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timestamp: true
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}
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});
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// Option 2: Fetch from Drift/Pyth price feed history
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// (if BlockedSignal doesn't have OHLC data)
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return signals.map(s => ({
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open: s.price, // Approximate - may need actual OHLC
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high: s.price + s.atr,
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low: s.price - s.atr,
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close: s.price,
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timestamp: s.timestamp
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}));
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}
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```
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### Option B: Add to Position Manager (Alternative)
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**File:** `lib/trading/position-manager.ts`
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**Add check in entry logic before opening position:**
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```typescript
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// Before: await driftClient.openPosition(...)
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const instantReversalCheck = await checkInstantReversalRisk(
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symbol, direction, entryPrice, stopLoss
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);
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if (instantReversalCheck.blocked) {
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console.log(`⚠️ Position NOT opened: ${instantReversalCheck.reason}`);
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return { success: false, reason: 'INSTANT_REVERSAL_RISK' };
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}
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// Continue with normal position opening...
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```
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**Pros/Cons:**
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- **Option A (check-risk):** ✅ Blocks earlier, consistent with other filters, easier to test
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- **Option B (position-manager):** ✅ Has access to real-time price data, but later in pipeline
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**Recommendation:** Implement in check-risk endpoint (Option A) for consistency with HTF filter and quality threshold checks.
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---
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## Step 3: Environment Variables (if needed)
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Add to `.env`:
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```bash
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# Quality Score Optimization (Dec 18, 2025)
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MIN_SIGNAL_QUALITY_SCORE_LONG=95
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MIN_SIGNAL_QUALITY_SCORE_SHORT=95
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# Instant Reversal Filter (Dec 18, 2025)
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INSTANT_REVERSAL_DETECTION_ENABLED=true
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INSTANT_REVERSAL_THRESHOLD_CANDLES=1.5 # SL must be > 1.5 candles away
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```
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---
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## Step 4: Database Updates (if needed)
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**Add new block reason to BlockedSignal table:**
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Check if `blockReason` enum includes `INSTANT_REVERSAL_RISK`:
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```sql
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SELECT enumlabel
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FROM pg_enum
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WHERE enumtypid = (
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SELECT oid FROM pg_type WHERE typname = 'BlockReason'
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);
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```
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If not present, add it:
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```sql
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ALTER TYPE "BlockReason" ADD VALUE 'INSTANT_REVERSAL_RISK';
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```
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OR update Prisma schema:
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```prisma
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enum BlockReason {
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// ... existing reasons
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INSTANT_REVERSAL_RISK // Add this
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}
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```
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Then run:
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```bash
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npx prisma db push
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```
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---
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## Step 5: Testing Protocol
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### 5.1 Unit Tests (if test suite exists)
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Create `tests/instant-reversal-filter.test.ts`:
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```typescript
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describe('Instant Reversal Filter', () => {
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it('should block trades with SL < 1.5 candles', async () => {
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const result = await checkInstantReversalRisk(
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'SOL', 'LONG', 100, 99.5, // Entry $100, SL $99.50 (0.5%)
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[{ high: 101, low: 99, close: 100 }] // 2% range candle
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);
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expect(result.blocked).toBe(true);
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});
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it('should allow trades with SL > 1.5 candles', async () => {
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const result = await checkInstantReversalRisk(
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'SOL', 'LONG', 100, 98.5, // Entry $100, SL $98.50 (1.5%)
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[{ high: 101, low: 99, close: 100 }] // 2% range candle
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);
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expect(result.blocked).toBe(false);
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});
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});
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```
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Run:
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```bash
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npm test -- instant-reversal-filter.test.ts
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```
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### 5.2 Integration Test (Manual)
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1. **Trigger a test signal:**
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- Send webhook to n8n with quality score 95
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- Verify: Trade executes (quality threshold passed)
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2. **Check BlockedSignal table:**
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```sql
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SELECT * FROM "BlockedSignal"
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WHERE "blockReason" = 'INSTANT_REVERSAL_RISK'
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ORDER BY timestamp DESC
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LIMIT 10;
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```
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3. **Verify logs:**
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- Check container logs: `docker logs trading-bot-v4 --tail 100`
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- Look for: `⚠️ BLOCKED: Instant reversal risk` or `✅ Quality: 95 → Trade approved`
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### 5.3 Paper Trade (if available)
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- Switch to testnet/paper mode
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- Run for 24 hours
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- Verify: Fewer trades executed (~0.44/day vs 1.0/day)
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- Check: Quality scores of executed trades all >=95
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---
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## Step 6: Deployment
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### 6.1 Commit Changes
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```bash
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cd /home/icke/traderv4
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# Stage changes
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git add lib/trading/signal-quality.ts
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git add app/api/check-risk/route.ts # Or wherever instant reversal filter added
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git add .env # If ENV vars changed
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git add docs/STRATEGY_OPTIMIZATION_DEC_2025.md
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git add docs/IMPLEMENTATION_GUIDE.md
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git add .github/copilot-instructions.md
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# Commit
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git commit -m "feat: Implement Q>=95 quality threshold + instant reversal filter
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- Update quality thresholds: LONG 90→95, SHORT 80→95
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- Add instant reversal detection (blocks SL <1.5 candles)
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- Validated performance: 11 trades, 63.6% WR, +183.4% return, 3.88 PF
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- Ref: docs/STRATEGY_OPTIMIZATION_DEC_2025.md"
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# Push
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git push origin main
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```
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### 6.2 Restart Container
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```bash
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# Rebuild and restart
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docker compose down
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docker compose up -d --build
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# Verify container started
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docker ps | grep trading-bot-v4
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# Check logs
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docker logs trading-bot-v4 --tail 50 --follow
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```
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### 6.3 Verify Deployment
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```bash
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# 1. Check container timestamp
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docker inspect trading-bot-v4 | grep Created
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# 2. Verify commit deployed
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docker exec trading-bot-v4 git log -1 --oneline
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# 3. Test health endpoint
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curl http://localhost:3000/api/health
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# 4. Check ENV vars
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docker exec trading-bot-v4 printenv | grep QUALITY
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```
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---
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## Step 7: Post-Deployment Monitoring
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### Day 1 Checklist
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- [ ] Monitor logs every 2 hours for first 24h
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- [ ] Check for any Q>=95 signals received
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- [ ] Verify instant reversal filter triggers (if any)
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- [ ] Confirm first trade execution (quality logged correctly)
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- [ ] Check database: `SELECT * FROM "Trade" ORDER BY entryTime DESC LIMIT 3;`
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- [ ] Review BlockedSignal: `SELECT blockReason, COUNT(*) FROM "BlockedSignal" WHERE timestamp > NOW() - INTERVAL '1 day' GROUP BY blockReason;`
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### Week 1 Analysis
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After 7 days or first 3-5 trades:
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```sql
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-- Performance check
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WITH recent_trades AS (
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SELECT
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realizedPnL,
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CASE WHEN realizedPnL > 0 THEN 1 ELSE 0 END as is_win,
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signalQualityScore
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FROM "Trade"
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WHERE entryTime >= '2025-12-18' -- Deployment date
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AND exitTime IS NOT NULL
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AND timeframe = '5'
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)
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SELECT
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COUNT(*) as trades,
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ROUND(100.0 * SUM(is_win) / COUNT(*), 1) as win_rate_pct,
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ROUND(SUM(realizedPnL)::numeric, 2) as total_pnl,
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ROUND(AVG(CASE WHEN is_win=1 THEN realizedPnL END)::numeric, 2) as avg_win,
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ROUND(AVG(CASE WHEN is_win=0 THEN realizedPnL END)::numeric, 2) as avg_loss,
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ROUND(AVG(signalQualityScore)::numeric, 1) as avg_quality,
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MIN(signalQualityScore) as min_quality
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FROM recent_trades;
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```
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**Compare to validated backtest:**
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- Expected: ~3 trades (0.44/day × 7 days)
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- Expected WR: 60-65%
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- Expected avg win: ~$34
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- Expected avg loss: ~$21
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- Expected PF: 2.0+ (conservative), 3.88 (optimistic)
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**Alert if:**
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- ❌ Win rate <50%
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- ❌ Avg loss >$35
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- ❌ Profit factor <1.5
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- ❌ Zero trades in 5 days (threshold too strict)
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- ❌ Any quality score <95 (filter bypass bug)
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### Rollback Procedure (if needed)
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```bash
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# 1. Revert git commit
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git revert HEAD
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git push origin main
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# 2. Rebuild container
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docker compose down
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docker compose up -d --build
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# 3. Verify rollback
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docker logs trading-bot-v4 | grep "Quality threshold"
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# Should show: LONG=90, SHORT=80 (old values)
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# 4. Document failure
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# Add notes to docs/STRATEGY_OPTIMIZATION_DEC_2025.md under "Rollback Criteria"
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```
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---
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## Quick Reference Commands
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```bash
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# Check logs
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docker logs trading-bot-v4 --tail 100 --follow
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# Recent trades
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docker exec trading-bot-v4 psql $DATABASE_URL -c "
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SELECT entryTime, direction, realizedPnL, exitReason, signalQualityScore
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FROM \"Trade\"
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WHERE entryTime >= '2025-12-18'
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ORDER BY entryTime DESC
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LIMIT 10;
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"
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# Blocked signals today
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docker exec trading-bot-v4 psql $DATABASE_URL -c "
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SELECT blockReason, COUNT(*)
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FROM \"BlockedSignal\"
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WHERE timestamp > CURRENT_DATE
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GROUP BY blockReason;
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"
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# Quality score distribution (last 24h)
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docker exec trading-bot-v4 psql $DATABASE_URL -c "
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SELECT
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CASE
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WHEN \"qualityScore\" >= 95 THEN '95+'
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WHEN \"qualityScore\" >= 90 THEN '90-94'
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WHEN \"qualityScore\" >= 85 THEN '85-89'
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ELSE '<85'
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END as quality_bucket,
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COUNT(*)
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FROM \"BlockedSignal\"
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WHERE timestamp > NOW() - INTERVAL '24 hours'
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GROUP BY quality_bucket
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ORDER BY quality_bucket DESC;
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"
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# Restart if needed
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docker restart trading-bot-v4
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```
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---
|
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|
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## Success Criteria (After 25 trades or 60 days)
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|
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✅ **Strategy validated if:**
|
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1. Win rate >= 55%
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2. Profit factor >= 1.5
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3. Average loss <= $35
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4. Total P&L positive
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5. No catastrophic losses (>$100 single trade)
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|
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❌ **Strategy failed if:**
|
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1. Win rate < 40%
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2. Profit factor < 0.8
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3. Average loss > $50
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4. Total drawdown > 50%
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5. Multiple instant reversal filter bypasses (bugs)
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---
|
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|
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## Contact & Support
|
||
|
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- **Documentation:** `docs/STRATEGY_OPTIMIZATION_DEC_2025.md`
|
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- **Code Locations:**
|
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- Quality thresholds: `lib/trading/signal-quality.ts`
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- Instant reversal: `app/api/check-risk/route.ts` (to be added)
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- HTF filter: (existing, no changes)
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- 5-candle exit: Position Manager (existing, no changes)
|
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- **User Approval:** Obtained Dec 18, 2025
|
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- **Questions:** Review conversation history or ask user
|
||
|
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---
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**Last Updated:** December 18, 2025
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**Status:** 📋 Documentation complete, ready for implementation
|
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**Next Step:** Begin Step 1 (Update quality thresholds)
|