d3c04ea9c9
- Add Position Manager state persistence to survive restarts - Auto-restore open trades from database on startup - Save state after TP1, SL adjustments, profit locks - Persist to configSnapshot JSON field - Add automatic order cancellation - Cancel all TP/SL orders when position fully closed - New cancelAllOrders() function in drift/orders.ts - Prevents orphaned orders after manual closes - Improve stop loss management - Move SL to +0.35% after TP1 (was +0.15%) - Gives more breathing room for retracements - Still locks in half of TP1 profit - Add database sync when Position Manager closes trades - Auto-update Trade record with exit data - Save P&L, exit reason, hold time - Fix analytics showing stale data - Add trade state management functions - updateTradeState() for Position Manager persistence - getOpenTrades() for startup restoration - getInitializedPositionManager() for async init - Create n8n database analytics workflows - Daily report workflow (automated at midnight) - Pattern analysis (hourly/daily performance) - Stop loss effectiveness analysis - Database analytics query workflow - Complete setup guide (N8N_DATABASE_SETUP.md)
140 lines
7.7 KiB
JSON
140 lines
7.7 KiB
JSON
{
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"name": "Pattern Analysis - Win Rate by Hour",
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"nodes": [
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{
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"parameters": {},
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"id": "1a2b3c4d-5e6f-7a8b-9c0d-1e2f3a4b5c6d",
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"name": "Manual Trigger",
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"type": "n8n-nodes-base.manualTrigger",
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"typeVersion": 1,
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"position": [240, 300]
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},
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{
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"parameters": {
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"operation": "executeQuery",
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"query": "-- Win rate analysis by hour of day\nSELECT \n EXTRACT(HOUR FROM \"entryTime\") as hour,\n COUNT(*) as total_trades,\n COUNT(CASE WHEN \"realizedPnL\" > 0 THEN 1 END) as wins,\n COUNT(CASE WHEN \"realizedPnL\" < 0 THEN 1 END) as losses,\n ROUND(COUNT(CASE WHEN \"realizedPnL\" > 0 THEN 1 END)::numeric / NULLIF(COUNT(*), 0) * 100, 2) as win_rate_pct,\n ROUND(SUM(\"realizedPnL\")::numeric, 2) as total_pnl,\n ROUND(AVG(\"realizedPnL\")::numeric, 4) as avg_pnl\nFROM \"Trade\"\nWHERE status = 'closed'\n AND \"isTestTrade\" = false\n AND \"entryTime\" >= NOW() - INTERVAL '30 days'\nGROUP BY EXTRACT(HOUR FROM \"entryTime\")\nORDER BY hour;"
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},
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"id": "2b3c4d5e-6f7a-8b9c-0d1e-2f3a4b5c6d7e",
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"name": "Query Hourly Performance",
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"type": "n8n-nodes-base.postgres",
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"typeVersion": 2.4,
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"position": [460, 300],
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"credentials": {
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"postgres": {
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"id": "1",
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"name": "Trading Bot Database"
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}
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}
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},
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{
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"parameters": {
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"operation": "executeQuery",
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"query": "-- Win rate by day of week\nSELECT \n EXTRACT(DOW FROM \"entryTime\") as day_of_week,\n CASE EXTRACT(DOW FROM \"entryTime\")\n WHEN 0 THEN 'Sunday'\n WHEN 1 THEN 'Monday'\n WHEN 2 THEN 'Tuesday'\n WHEN 3 THEN 'Wednesday'\n WHEN 4 THEN 'Thursday'\n WHEN 5 THEN 'Friday'\n WHEN 6 THEN 'Saturday'\n END as day_name,\n COUNT(*) as total_trades,\n COUNT(CASE WHEN \"realizedPnL\" > 0 THEN 1 END) as wins,\n ROUND(COUNT(CASE WHEN \"realizedPnL\" > 0 THEN 1 END)::numeric / NULLIF(COUNT(*), 0) * 100, 2) as win_rate_pct,\n ROUND(SUM(\"realizedPnL\")::numeric, 2) as total_pnl\nFROM \"Trade\"\nWHERE status = 'closed'\n AND \"isTestTrade\" = false\n AND \"entryTime\" >= NOW() - INTERVAL '30 days'\nGROUP BY EXTRACT(DOW FROM \"entryTime\")\nORDER BY day_of_week;"
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},
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"id": "3c4d5e6f-7a8b-9c0d-1e2f-3a4b5c6d7e8f",
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"name": "Query Daily Performance",
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"type": "n8n-nodes-base.postgres",
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"typeVersion": 2.4,
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"position": [460, 500],
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"credentials": {
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"postgres": {
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"id": "1",
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"name": "Trading Bot Database"
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}
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}
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},
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{
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"parameters": {
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"operation": "executeQuery",
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"query": "-- Hold time vs profitability\nSELECT \n CASE \n WHEN \"holdTimeSeconds\" < 300 THEN '0-5 min'\n WHEN \"holdTimeSeconds\" < 900 THEN '5-15 min'\n WHEN \"holdTimeSeconds\" < 1800 THEN '15-30 min'\n WHEN \"holdTimeSeconds\" < 3600 THEN '30-60 min'\n WHEN \"holdTimeSeconds\" < 7200 THEN '1-2 hours'\n ELSE '2+ hours'\n END as hold_time_bucket,\n COUNT(*) as trades,\n COUNT(CASE WHEN \"realizedPnL\" > 0 THEN 1 END) as wins,\n ROUND(COUNT(CASE WHEN \"realizedPnL\" > 0 THEN 1 END)::numeric / NULLIF(COUNT(*), 0) * 100, 2) as win_rate_pct,\n ROUND(AVG(\"realizedPnL\")::numeric, 4) as avg_pnl,\n ROUND(SUM(\"realizedPnL\")::numeric, 2) as total_pnl\nFROM \"Trade\"\nWHERE status = 'closed'\n AND \"isTestTrade\" = false\n AND \"holdTimeSeconds\" IS NOT NULL\n AND \"entryTime\" >= NOW() - INTERVAL '30 days'\nGROUP BY \n CASE \n WHEN \"holdTimeSeconds\" < 300 THEN '0-5 min'\n WHEN \"holdTimeSeconds\" < 900 THEN '5-15 min'\n WHEN \"holdTimeSeconds\" < 1800 THEN '15-30 min'\n WHEN \"holdTimeSeconds\" < 3600 THEN '30-60 min'\n WHEN \"holdTimeSeconds\" < 7200 THEN '1-2 hours'\n ELSE '2+ hours'\n END\nORDER BY \n CASE \n WHEN hold_time_bucket = '0-5 min' THEN 1\n WHEN hold_time_bucket = '5-15 min' THEN 2\n WHEN hold_time_bucket = '15-30 min' THEN 3\n WHEN hold_time_bucket = '30-60 min' THEN 4\n WHEN hold_time_bucket = '1-2 hours' THEN 5\n ELSE 6\n END;"
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},
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"id": "4d5e6f7a-8b9c-0d1e-2f3a-4b5c6d7e8f9a",
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"name": "Query Hold Time Analysis",
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"type": "n8n-nodes-base.postgres",
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"typeVersion": 2.4,
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"position": [460, 700],
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"credentials": {
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"postgres": {
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"id": "1",
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"name": "Trading Bot Database"
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}
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}
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},
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{
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"parameters": {
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"jsCode": "const hourly = $('Query Hourly Performance').all().map(item => item.json);\nconst daily = $('Query Daily Performance').all().map(item => item.json);\nconst holdTime = $('Query Hold Time Analysis').all().map(item => item.json);\n\n// Find best and worst hours\nconst sortedHours = [...hourly].sort((a, b) => b.win_rate_pct - a.win_rate_pct);\nconst bestHours = sortedHours.slice(0, 3);\nconst worstHours = sortedHours.slice(-3).reverse();\n\n// Find best day\nconst sortedDays = [...daily].sort((a, b) => b.win_rate_pct - a.win_rate_pct);\nconst bestDay = sortedDays[0];\nconst worstDay = sortedDays[sortedDays.length - 1];\n\n// Find optimal hold time\nconst sortedHoldTime = [...holdTime].sort((a, b) => b.avg_pnl - a.avg_pnl);\nconst optimalHoldTime = sortedHoldTime[0];\n\n// Generate insights\nconst insights = {\n hourly: {\n bestHours: bestHours.map(h => `${h.hour}:00 (${h.win_rate_pct}% win rate, ${h.total_trades} trades)`),\n worstHours: worstHours.map(h => `${h.hour}:00 (${h.win_rate_pct}% win rate, ${h.total_trades} trades)`),\n recommendation: bestHours.length > 0 ? `Focus trading around ${bestHours[0].hour}:00-${bestHours[2].hour}:00` : 'Need more data'\n },\n daily: {\n bestDay: bestDay ? `${bestDay.day_name} (${bestDay.win_rate_pct}% win rate)` : 'N/A',\n worstDay: worstDay ? `${worstDay.day_name} (${worstDay.win_rate_pct}% win rate)` : 'N/A',\n recommendation: bestDay && worstDay ? `Trade more on ${bestDay.day_name}, avoid ${worstDay.day_name}` : 'Need more data'\n },\n holdTime: {\n optimal: optimalHoldTime ? `${optimalHoldTime.hold_time_bucket} (avg P&L: $${optimalHoldTime.avg_pnl})` : 'N/A',\n recommendation: optimalHoldTime ? `Target exits in ${optimalHoldTime.hold_time_bucket} range` : 'Need more data'\n },\n rawData: {\n hourly,\n daily,\n holdTime\n }\n};\n\nreturn [{ json: insights }];"
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},
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"id": "5e6f7a8b-9c0d-1e2f-3a4b-5c6d7e8f9a0b",
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"name": "Generate Insights",
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"type": "n8n-nodes-base.code",
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"typeVersion": 2,
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"position": [680, 300]
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}
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],
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"connections": {
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"Manual Trigger": {
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"main": [
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[
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{
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"node": "Query Hourly Performance",
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"type": "main",
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"index": 0
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},
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{
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"node": "Query Daily Performance",
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"type": "main",
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"index": 0
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},
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{
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"node": "Query Hold Time Analysis",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Query Hourly Performance": {
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"main": [
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[
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{
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"node": "Generate Insights",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Query Daily Performance": {
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"main": [
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[
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{
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"node": "Generate Insights",
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"type": "main",
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"index": 0
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}
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]
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]
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},
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"Query Hold Time Analysis": {
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"main": [
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[
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{
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"node": "Generate Insights",
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"type": "main",
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"index": 0
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}
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]
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]
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}
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},
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"pinData": {},
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"settings": {
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"executionOrder": "v1"
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},
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"staticData": null,
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"tags": [],
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"triggerCount": 0,
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"updatedAt": "2025-10-27T00:00:00.000Z",
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"versionId": "1"
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}
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