feat: Add roadmap page showing development progress
New Features: - /roadmap page with visual progress tracking - Shows all completed, in-progress, and planned features - Stats overview: total items, completion rate, status breakdown - Color-coded status indicators (green=complete, blue=in-progress, gray=planned) API Endpoint: - GET /api/roadmap returns structured roadmap data - 15 major features documented across 7 phases - Each item includes: title, status, description, impact, completion date, implementation details Documented Features: Phase 1-3: Core system, TP2 runner, ATR-based risk, ADX adaptive, quality filtering, 5-layer DB protection Overall Progress: 11/15 complete (73% completion rate) Files Added: - app/roadmap/page.tsx (frontend) - app/api/roadmap/route.ts (backend)
This commit is contained in:
mindesbunister
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app/api/roadmap/route.ts
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298
app/api/roadmap/route.ts
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import { NextResponse } from 'next/server'
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export async function GET() {
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const roadmap = [
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// Phase 1: Foundation (COMPLETE)
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{
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phase: 'Phase 1',
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title: 'Core Trading System',
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status: 'complete',
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description: 'Drift Protocol integration, Position Manager, TP/SL automation, database tracking',
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impact: 'Fully automated trading with position monitoring and exit management',
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completed: 'Nov 2024',
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items: [
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'Drift SDK integration with transaction confirmation',
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'Position Manager with 2-second monitoring loop',
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'Database persistence with Prisma ORM',
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'On-chain TP/SL order placement',
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'Telegram notifications for trade events',
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'n8n webhook integration for TradingView signals'
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]
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},
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{
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phase: 'Phase 1',
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title: 'TP2-as-Runner System',
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status: 'complete',
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description: 'Configurable TP1 (60% default) + Runner (40%) with trailing stop',
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impact: '5x larger runner position capturing extended trend moves',
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completed: 'Nov 11, 2025',
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items: [
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'Configurable TP1 close percentage (TAKE_PROFIT_1_SIZE_PERCENT)',
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'TP2 activates trailing stop instead of closing',
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'Dynamic runner size calculation (100% - TP1%)',
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'ATR-based trailing stop with profit acceleration',
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'Settings UI shows dynamic runner percentage'
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]
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},
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{
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phase: 'Phase 1',
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title: 'ATR-Based Risk Management',
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status: 'complete',
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description: 'Regime-agnostic TP/SL system adapting to market volatility',
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impact: 'Auto-adjusts targets: bull markets expand, bear markets tighten',
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completed: 'Nov 17, 2025',
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items: [
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'ATR × multipliers for TP1 (2.0x), TP2 (4.0x), SL (3.0x)',
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'Safety bounds prevent extreme targets',
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'Asset-agnostic (SOL vs BTC different ATR)',
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'Fallback to fixed % when ATR unavailable',
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'TradingView integration passes ATR field'
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]
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},
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{
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phase: 'Phase 1',
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title: 'ADX-Based Adaptive Systems',
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status: 'complete',
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description: 'Trend-strength aware runner SL and trailing stop multipliers',
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impact: 'Strong trends get wider trail, weak trends protect capital',
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completed: 'Nov 19, 2025',
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items: [
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'Runner SL: ADX <20 = breakeven, 20-25 = -0.3%, >25 = -0.55%',
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'Trailing stop multipliers: ADX >30 = 1.5×, 25-30 = 1.25×, <25 = 1.0×',
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'Profit acceleration: >2% profit adds 1.3× multiplier',
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'Backward compatible (trades without ADX use base values)',
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'Graduated approach prevents binary decisions'
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]
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},
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// Phase 2: Quality Filtering (COMPLETE)
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{
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phase: 'Phase 2',
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title: 'Signal Quality Scoring System',
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status: 'complete',
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description: 'Multi-factor signal evaluation (ATR, ADX, RSI, Volume, Price Position)',
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impact: '0-100 score filtering low-quality setups, data-driven optimization',
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completed: 'Nov 11, 2025',
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items: [
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'Timeframe-aware scoring (5min vs daily thresholds)',
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'Component breakdown stored in database',
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'BlockedSignal table tracks filtered signals',
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'Version tracking for scoring algorithm evolution',
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'Anti-chop filter (-20 points for extreme sideways)'
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]
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},
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{
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phase: 'Phase 2',
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title: 'Direction-Specific Quality Thresholds',
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status: 'complete',
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description: 'LONG 90+, SHORT 95+ based on historical win rate analysis',
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impact: 'Blocks $847 in losses while missing only $210 in wins (+$637 net)',
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completed: 'Nov 23, 2025',
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items: [
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'Historical analysis: Quality 90-94 shorts = 28.6% WR (-$553.76)',
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'Historical analysis: Quality 90-94 longs = 71.4% WR (+$44.77)',
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'Direction-specific ENV variables',
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'Top 2 biggest losses (-$524.97) blocked by 95+ threshold',
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'3:1 loss avoidance ratio validated (Nov 24 analysis)'
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]
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},
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{
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phase: 'Phase 2',
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title: 'Adaptive Leverage System',
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status: 'complete',
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description: 'Quality-based position sizing (95+ = 15x, 90-94 = 10x)',
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impact: 'Risk-adjusted positions: borderline signals get 33% less exposure',
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completed: 'Nov 24, 2025',
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items: [
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'Quality threshold at 95 (configurable)',
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'High quality: 15x leverage, Low quality: 10x leverage',
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'Early quality calculation before position sizing',
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'Logging shows adaptive leverage decisions',
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'ENV configuration: USE_ADAPTIVE_LEVERAGE=true'
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]
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},
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// Phase 3: Robustness (COMPLETE)
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{
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phase: 'Phase 3',
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title: '5-Layer Database Protection',
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status: 'complete',
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description: 'Persistent logging, retry logic, orphan detection, auto-recovery',
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impact: 'Zero data loss guarantee - all trades tracked even on failures',
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completed: 'Nov 21, 2025',
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items: [
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'Persistent file logger (survives container restarts)',
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'Retry + verification logic (3 attempts with backoff)',
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'Orphan position detection on every startup',
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'Retroactive record creation for missing trades',
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'Telegram alerts for recovered positions'
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]
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},
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{
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phase: 'Phase 3',
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title: 'Ghost Position Protection',
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status: 'complete',
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description: '3-layer ghost detection preventing unmonitored positions',
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impact: 'Self-healing system catches state drift within 5 minutes',
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completed: 'Nov 15, 2025',
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items: [
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'Layer 1: Drift API validation (every 5 minutes)',
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'Layer 2: Death spiral detector (20+ failed close attempts)',
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'Layer 3: Monitoring loop checks (every 40 seconds)',
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'Automatic ghost cleanup with P&L calculation',
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'No manual intervention required'
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]
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},
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{
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phase: 'Phase 3',
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title: 'Rate Limit Handling',
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status: 'complete',
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description: 'Exponential backoff retry logic for Solana RPC operations',
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impact: '99% of transient failures auto-recover, prevents missed trades',
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completed: 'Nov 14, 2025',
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items: [
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'Retry with exponential backoff (5s → 10s → 20s)',
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'Applies to all order operations (open, close, cancel)',
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'Database logging of rate limit events',
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'Analytics endpoint for monitoring patterns',
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'Position Manager keeps monitoring on 429 errors'
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]
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},
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// Phase 4: Data Collection (IN PROGRESS)
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{
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phase: 'Phase 4',
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title: 'Multi-Timeframe Analysis',
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status: 'in-progress',
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description: 'Parallel data collection: 5min (execute) vs 15min/1H/4H/Daily (track)',
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impact: 'Determine which timeframe has best win rate for live trading',
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items: [
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'BlockedSignalTracker monitors non-5min signals',
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'Tracks price movements at 1/5/15/30 minute intervals',
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'Detects if TP1/TP2/SL would have been hit',
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'Records MFE/MAE for 30-minute window',
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'Target: 50+ signals per timeframe before analysis'
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]
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},
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{
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phase: 'Phase 4',
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title: 'Quality Threshold Validation',
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status: 'in-progress',
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description: 'Track quality-blocked signals to validate 90/95 thresholds',
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impact: 'Data-driven proof if thresholds filter winners or losers',
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items: [
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'BlockedSignalTracker monitors QUALITY_SCORE_TOO_LOW signals',
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'Same price tracking as multi-timeframe analysis',
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'Target: 20-30 blocked signals over 2-4 weeks',
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'Compare win rate vs executed trades in same range',
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'Adjust thresholds if blocked signals >50% win rate'
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]
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},
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// Phase 5: Enhancement (PLANNED)
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{
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phase: 'Phase 5',
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title: 'Stop Hunt Revenge System',
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status: 'complete',
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description: 'Auto re-entry after high-quality stop-outs when price reverses',
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impact: 'Capture reversals after stop hunts on quality 85+ signals',
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completed: 'Nov 20, 2025',
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items: [
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'4-hour revenge window monitoring',
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'Quality 85+ signals eligible',
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'1.0× position size (same as original)',
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'One revenge per stop hunt',
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'30-second price checks for active stop hunts',
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'Database tracking with StopHunt table'
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]
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},
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{
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phase: 'Phase 5',
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title: 'MAE/MFE Analysis Dashboard',
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status: 'planned',
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description: 'Visualize Maximum Adverse/Favorable Excursion for TP/SL optimization',
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impact: 'Data-driven adjustment of target distances based on actual price action',
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items: [
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'Chart showing MFE distribution (how far trades go in profit)',
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'Chart showing MAE distribution (how far trades go in drawdown)',
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'Identify optimal TP1/TP2 levels to capture 80% of MFE',
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'Identify optimal SL level to avoid 80% of MAE',
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'Compare current targets vs optimal targets',
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'A/B test adjusted targets on separate indicator version'
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]
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},
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{
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phase: 'Phase 5',
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title: 'Market Regime Detection',
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status: 'planned',
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description: 'Dynamic quality threshold adjustment based on ADX trends',
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impact: 'Adapt to market conditions: raise thresholds in chop, lower in trends',
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items: [
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'Multi-timeframe ADX analysis (1H + 4H)',
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'If ADX <20 on both: raise all thresholds +5 points',
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'If ADX >25 on both: lower thresholds -5 points',
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'Separate filters for range-bound vs trending markets',
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'Telegram alerts when regime changes detected'
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]
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},
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// Phase 6: Scaling (FUTURE)
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{
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phase: 'Phase 6',
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title: 'Multi-Symbol Support',
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status: 'planned',
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description: 'Trade SOL, ETH, BTC simultaneously with independent configs',
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impact: 'Diversification reduces single-asset risk, 3× opportunity frequency',
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items: [
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'Per-symbol enable/disable toggles',
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'Independent position sizing and leverage',
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'Separate quality thresholds per symbol',
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'Symbol-specific cooldown periods',
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'Drift market config for each asset'
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]
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},
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{
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phase: 'Phase 6',
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title: 'High Availability Setup',
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status: 'planned',
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description: 'Failover system with health checks and automatic recovery',
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impact: '99.9% uptime guarantee, no missed trades during restarts',
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items: [
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'Primary + backup bot instances',
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'Database replication (primary/replica)',
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'Health check monitoring (60-second intervals)',
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'Automatic failover on primary failure',
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'Telegram alerts for failover events',
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'Systemd service for auto-restart'
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]
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},
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// Phase 7: Intelligence (DISTANT FUTURE)
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{
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phase: 'Phase 7',
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title: 'ML-Based Quality Scoring',
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status: 'planned',
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description: 'Machine learning model optimizes component weights based on outcomes',
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impact: 'Automatic adaptation to changing market conditions',
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items: [
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'Collect 500+ trades with outcomes for training data',
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'Feature engineering: ADX, ATR, RSI, Volume, Price Position',
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'Train gradient boosting model (XGBoost/LightGBM)',
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'Predict win probability instead of fixed score',
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'Retrain monthly on new data',
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'A/B test ML scores vs rule-based scores'
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]
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},
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]
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return NextResponse.json({
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success: true,
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roadmap,
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stats: {
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total: roadmap.length,
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complete: roadmap.filter(item => item.status === 'complete').length,
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inProgress: roadmap.filter(item => item.status === 'in-progress').length,
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planned: roadmap.filter(item => item.status === 'planned').length,
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}
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})
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}
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