feat: Position Manager persistence + order cleanup + improved stop loss
- 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)
This commit is contained in:
mindesbunister
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N8N_DATABASE_SETUP.md
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317
N8N_DATABASE_SETUP.md
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# n8n Database Integration Setup Guide
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## Overview
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This guide shows you how to connect your n8n instance to the Trading Bot v4 PostgreSQL database for automated analysis and insights.
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## Database Connection Details
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⚠️ **IMPORTANT:** n8n is on a **different Docker network** than the trading bot postgres. You MUST use the host machine IP or localhost.
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### ✅ CORRECT Connection (n8n is on different network)
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```
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Type: PostgreSQL
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Host: host.docker.internal (or your machine's IP like 172.18.0.1)
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Port: 5432
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Database: trading_bot_v4
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User: postgres
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Password: postgres
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SSL Mode: disable
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```
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### Alternative: Use localhost with host networking
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If `host.docker.internal` doesn't work, find your docker network gateway:
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```bash
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docker inspect n8n --format '{{range .NetworkSettings.Networks}}{{.Gateway}}{{end}}'
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# Result: 172.18.0.1 (use this as Host)
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```
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### Network Details (for reference)
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- **n8n network:** `compose_files_default` (172.18.0.0/16)
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- **Trading bot network:** `traderv4_trading-net` (172.28.0.0/16)
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- **PostgreSQL container:** `trading-bot-postgres` on traderv4_trading-net (172.28.0.2)
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- **PostgreSQL exposed port:** 5432 → localhost:5432
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Since they're on different networks, use the **host machine as bridge**.
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## Setup Steps
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### 1. Access n8n
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Open your browser and navigate to:
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```
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http://localhost:8098
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```
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### 2. Create PostgreSQL Credential
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1. Click on **Credentials** in the left sidebar
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2. Click **Add Credential**
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3. Search for **Postgres** and select it
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4. Fill in the connection details (see above)
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5. Name it: **Trading Bot Database**
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6. Click **Test Connection** to verify
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7. Click **Save**
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### 3. Import Workflows
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Four pre-built workflow templates are ready in your workspace:
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#### A. Database Analytics (n8n-database-analytics.json)
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**Purpose:** Query and analyze closed trades with statistical calculations
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**Features:**
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- Fetches last 100 closed trades
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- Calculates win rate, P&L, profit factor
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- Breaks down by symbol, direction, and exit reason
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- Identifies best performing setups
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**To import:**
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1. Go to **Workflows** → **Add Workflow**
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2. Click **...** menu → **Import from File**
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3. Select `n8n-database-analytics.json`
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4. Update PostgreSQL node to use "Trading Bot Database" credential
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5. Click **Save**
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6. Click **Execute Workflow** to test
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#### B. Daily Trading Report (n8n-daily-report.json)
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**Purpose:** Automated daily summary at midnight (stores in DailyStats table)
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**Features:**
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- Runs automatically at 00:05 every day
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- Calculates yesterday's performance
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- Breaks down by symbol
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- Stores in DailyStats table for historical tracking
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- Calculates win rate, profit factor, avg hold time
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**To import:**
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1. Import workflow from file
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2. Update both PostgreSQL nodes with "Trading Bot Database" credential
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3. **Activate** the workflow (toggle in top right)
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4. Will run automatically at midnight
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#### C. Pattern Analysis (n8n-pattern-analysis.json)
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**Purpose:** Discover which times/conditions produce best results
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**Features:**
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- **Hourly Analysis:** Which hours have best win rate
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- **Daily Analysis:** Which days perform best
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- **Hold Time Analysis:** Optimal position duration
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- Generates actionable recommendations
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**Example insights:**
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- "Focus trading around 14:00-16:00 (75% win rate)"
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- "Trade more on Tuesday, avoid Friday"
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- "Target exits in 15-30 min range"
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**To import:**
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1. Import workflow
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2. Update all 3 PostgreSQL nodes with credential
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3. Run manually to see insights
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#### D. Stop Loss Analysis (n8n-stop-loss-analysis.json)
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**Purpose:** Optimize stop loss distances and understand exit patterns
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**Features:**
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- Exit reason breakdown (stopped out vs targets hit)
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- Stop distance effectiveness (tight vs wide stops)
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- Symbol-specific stop performance
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- Calculates profit factor (avg win / avg loss)
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- Recommendations for stop optimization
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**Example insights:**
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- "⚠️ High stop hit rate - consider wider stops"
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- "💡 Normal (1-1.5%) stops perform 45% better than tight stops"
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- "✅ Risk/reward ratio is positive"
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**To import:**
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1. Import workflow
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2. Update all 3 PostgreSQL nodes with credential
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3. Run manually to analyze
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## Database Schema Reference
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### Trade Table (Main table)
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Key fields for analysis:
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```sql
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id, symbol, direction, entryPrice, exitPrice, quantity,
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notionalSize, realizedPnL, realizedPnLPercent,
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entryTime, exitTime, holdTimeSeconds,
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stopLossPrice, takeProfitPrice1, takeProfitPrice2,
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exitReason, status, isTestTrade
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```
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### Common Queries
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#### Get all closed trades (last 30 days)
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```sql
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SELECT * FROM "Trade"
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WHERE status = 'closed'
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AND "isTestTrade" = false
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AND "entryTime" >= NOW() - INTERVAL '30 days'
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ORDER BY "entryTime" DESC;
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```
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#### Calculate win rate
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```sql
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SELECT
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COUNT(*) as total_trades,
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COUNT(CASE WHEN "realizedPnL" > 0 THEN 1 END) as wins,
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ROUND(COUNT(CASE WHEN "realizedPnL" > 0 THEN 1 END)::numeric / COUNT(*) * 100, 2) as win_rate
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FROM "Trade"
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WHERE status = 'closed' AND "isTestTrade" = false;
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```
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#### Best performing symbols
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```sql
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SELECT
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symbol,
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COUNT(*) as trades,
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SUM("realizedPnL") as total_pnl,
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AVG("realizedPnL") as avg_pnl
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FROM "Trade"
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WHERE status = 'closed' AND "isTestTrade" = false
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GROUP BY symbol
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ORDER BY total_pnl DESC;
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```
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## Workflow Automation Ideas
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### 1. Performance Alerts
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**Trigger:** Schedule (every 6 hours)
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**Query:** Check if win rate drops below 50% in last 24h
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**Action:** Send Telegram notification to pause trading
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### 2. Best Setup Detector
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**Trigger:** Manual or daily
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**Query:** Find symbol + direction + time combinations with >70% win rate
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**Action:** Save insights to config for bot to prioritize
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### 3. Drawdown Monitor
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**Trigger:** After each trade (webhook)
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**Query:** Calculate rolling 10-trade P&L
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**Action:** Auto-reduce position size if in drawdown
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### 4. Exit Optimization
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**Trigger:** Weekly
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**Query:** Compare TP1 vs TP2 hit rates and P&L
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**Action:** Recommend adjustment to TP levels
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## Connecting Workflows to Trading Bot
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### Webhook from Trading Bot to n8n
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In your n8n workflow:
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1. Add **Webhook** trigger node
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2. Set HTTP Method: POST
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3. Note the webhook URL: `http://localhost:8098/webhook/your-unique-id`
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In trading bot code (e.g., after trade closes):
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```typescript
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// Send trade data to n8n for analysis
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await fetch('http://localhost:8098/webhook/your-unique-id', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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tradeId: trade.id,
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symbol: trade.symbol,
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pnl: trade.realizedPnL,
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exitReason: trade.exitReason
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})
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});
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```
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### Update Bot Config from n8n
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In your n8n workflow (after analysis):
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1. Add **HTTP Request** node
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2. URL: `http://trading-bot-v4:3000/api/settings`
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3. Method: POST
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4. Body: Updated config based on analysis
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Example - adjust stop loss based on analysis:
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```json
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{
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"STOP_LOSS_PERCENT": 1.5,
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"USE_DUAL_STOPS": true
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}
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```
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## Advanced Use Cases
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### Machine Learning Integration
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Use n8n to:
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1. Export trade data to CSV
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2. Send to Python ML service via HTTP
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3. Receive predictions
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4. Update bot configuration
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### Multi-Timeframe Analysis
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Create workflow that:
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1. Queries trades by hour/day/week
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2. Identifies patterns at each timeframe
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3. Generates trading schedule recommendations
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### Risk Management Automation
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Build workflow that:
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1. Monitors account balance
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2. Calculates daily/weekly profit target
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3. Auto-pauses bot after hitting target
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4. Resumes trading next day/week
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## Troubleshooting
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### Connection Refused
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- Verify PostgreSQL container is running: `docker ps | grep postgres`
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- Check port mapping: `docker port trading-bot-postgres`
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- Ensure n8n and postgres are on same Docker network
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### Query Timeouts
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- Add indexes to frequently queried columns
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- Limit result sets with `LIMIT` clause
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- Use date range filters to reduce dataset
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### Empty Results
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- Check `isTestTrade` filter (you may want to include test trades for testing)
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- Verify date range in queries
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- Ensure trades have been closed (`status = 'closed'`)
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## Testing Your Setup
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### Quick Test Query
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In n8n, create a workflow with:
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1. Manual Trigger
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2. PostgreSQL node with query:
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```sql
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SELECT COUNT(*) as total_trades,
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MAX("entryTime") as last_trade
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FROM "Trade";
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```
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3. Execute and verify results
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### Verify Test Trade Flag
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```sql
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SELECT
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"isTestTrade",
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COUNT(*) as count
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FROM "Trade"
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GROUP BY "isTestTrade";
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```
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Expected output:
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- `false`: Production trades
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- `true`: Test trades from /api/trading/test-db
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## Next Steps
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1. **Import all 4 workflows** and test each one
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2. **Activate the Daily Report** workflow for automated tracking
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3. **Run Pattern Analysis** to discover your best trading times
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4. **Run Stop Loss Analysis** to optimize risk management
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5. **Create custom workflows** based on your specific needs
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## Support
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If you encounter issues:
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1. Check n8n logs: `docker logs n8n`
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2. Check postgres logs: `docker logs trading-bot-postgres`
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3. Test database connection from host: `psql -h localhost -p 5432 -U postgres -d trading_bot_v4`
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4. Verify bot is writing to database: Check `/analytics` page in web UI
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---
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**Pro Tip:** Start with the Pattern Analysis workflow to understand your trading patterns, then use those insights to create automated optimization workflows!
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@@ -10,7 +10,7 @@ import { initializeDriftService } from '@/lib/drift/client'
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import { openPosition, placeExitOrders } from '@/lib/drift/orders'
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import { normalizeTradingViewSymbol } from '@/config/trading'
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import { getMergedConfig } from '@/config/trading'
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import { getPositionManager, ActiveTrade } from '@/lib/trading/position-manager'
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import { getInitializedPositionManager, ActiveTrade } from '@/lib/trading/position-manager'
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import { createTrade } from '@/lib/database/trades'
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export interface ExecuteTradeRequest {
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@@ -209,7 +209,7 @@ export async function POST(request: NextRequest): Promise<NextResponse<ExecuteTr
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}
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// Add to position manager for monitoring
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const positionManager = getPositionManager()
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const positionManager = await getInitializedPositionManager()
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await positionManager.addTrade(activeTrade)
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console.log('✅ Trade added to position manager for monitoring')
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@@ -45,6 +45,19 @@ export interface CreateTradeParams {
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isTestTrade?: boolean
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}
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export interface UpdateTradeStateParams {
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positionId: string
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currentSize: number
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tp1Hit: boolean
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slMovedToBreakeven: boolean
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slMovedToProfit: boolean
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stopLossPrice: number
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realizedPnL: number
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unrealizedPnL: number
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peakPnL: number
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lastPrice: number
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}
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export interface UpdateTradeExitParams {
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positionId: string
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exitPrice: number
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@@ -144,6 +157,66 @@ export async function updateTradeExit(params: UpdateTradeExitParams) {
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}
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}
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/**
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* Update active trade state (for Position Manager persistence)
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*/
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export async function updateTradeState(params: UpdateTradeStateParams) {
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const prisma = getPrismaClient()
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try {
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const trade = await prisma.trade.update({
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where: { positionId: params.positionId },
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data: {
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// Store Position Manager state in configSnapshot
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configSnapshot: {
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...(await prisma.trade.findUnique({
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where: { positionId: params.positionId },
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select: { configSnapshot: true }
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}))?.configSnapshot as any,
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// Add Position Manager state
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positionManagerState: {
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currentSize: params.currentSize,
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tp1Hit: params.tp1Hit,
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slMovedToBreakeven: params.slMovedToBreakeven,
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slMovedToProfit: params.slMovedToProfit,
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stopLossPrice: params.stopLossPrice,
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realizedPnL: params.realizedPnL,
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unrealizedPnL: params.unrealizedPnL,
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peakPnL: params.peakPnL,
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lastPrice: params.lastPrice,
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lastUpdate: new Date().toISOString(),
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}
|
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}
|
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},
|
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})
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return trade
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} catch (error) {
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console.error('❌ Failed to update trade state:', error)
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// Don't throw - state updates are non-critical
|
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}
|
||||
}
|
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|
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/**
|
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* Get all open trades (for Position Manager recovery)
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*/
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export async function getOpenTrades() {
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const prisma = getPrismaClient()
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try {
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const trades = await prisma.trade.findMany({
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where: { status: 'open' },
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orderBy: { entryTime: 'asc' },
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})
|
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|
||||
console.log(`📊 Found ${trades.length} open trades to restore`)
|
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return trades
|
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} catch (error) {
|
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console.error('❌ Failed to get open trades:', error)
|
||||
return []
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}
|
||||
}
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|
||||
/**
|
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* Add price update for a trade (for tracking max gain/drawdown)
|
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*/
|
||||
|
||||
@@ -498,6 +498,15 @@ export async function closePosition(
|
||||
console.log(` Close price: $${oraclePrice.toFixed(4)}`)
|
||||
console.log(` Realized P&L: $${realizedPnL.toFixed(2)}`)
|
||||
|
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// If closing 100%, cancel all remaining orders for this market
|
||||
if (params.percentToClose === 100) {
|
||||
console.log('🗑️ Position fully closed, cancelling remaining orders...')
|
||||
const cancelResult = await cancelAllOrders(params.symbol)
|
||||
if (cancelResult.success && cancelResult.cancelledCount! > 0) {
|
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console.log(`✅ Cancelled ${cancelResult.cancelledCount} orders`)
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
success: true,
|
||||
transactionSignature: txSig,
|
||||
@@ -515,6 +524,68 @@ export async function closePosition(
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Cancel all open orders for a specific market
|
||||
*/
|
||||
export async function cancelAllOrders(
|
||||
symbol: string
|
||||
): Promise<{ success: boolean; cancelledCount?: number; error?: string }> {
|
||||
try {
|
||||
console.log(`🗑️ Cancelling all orders for ${symbol}...`)
|
||||
|
||||
const driftService = getDriftService()
|
||||
const driftClient = driftService.getClient()
|
||||
const marketConfig = getMarketConfig(symbol)
|
||||
|
||||
const isDryRun = process.env.DRY_RUN === 'true'
|
||||
if (isDryRun) {
|
||||
console.log('🧪 DRY RUN: Simulating order cancellation')
|
||||
return { success: true, cancelledCount: 0 }
|
||||
}
|
||||
|
||||
// Get user account to check for orders
|
||||
const userAccount = driftClient.getUserAccount()
|
||||
if (!userAccount) {
|
||||
throw new Error('User account not found')
|
||||
}
|
||||
|
||||
// Filter orders for this market
|
||||
const ordersToCancel = userAccount.orders.filter(
|
||||
(order: any) =>
|
||||
order.marketIndex === marketConfig.driftMarketIndex &&
|
||||
order.status === 0 // 0 = Open status
|
||||
)
|
||||
|
||||
if (ordersToCancel.length === 0) {
|
||||
console.log('✅ No open orders to cancel')
|
||||
return { success: true, cancelledCount: 0 }
|
||||
}
|
||||
|
||||
console.log(`📋 Found ${ordersToCancel.length} open orders to cancel`)
|
||||
|
||||
// Cancel all orders for this market
|
||||
const txSig = await driftClient.cancelOrders(
|
||||
undefined, // Cancel by market type
|
||||
marketConfig.driftMarketIndex,
|
||||
undefined // No specific direction filter
|
||||
)
|
||||
|
||||
console.log(`✅ Orders cancelled! Transaction: ${txSig}`)
|
||||
|
||||
return {
|
||||
success: true,
|
||||
cancelledCount: ordersToCancel.length,
|
||||
}
|
||||
|
||||
} catch (error) {
|
||||
console.error('❌ Failed to cancel orders:', error)
|
||||
return {
|
||||
success: false,
|
||||
error: error instanceof Error ? error.message : 'Unknown error',
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Close entire position for a market
|
||||
*/
|
||||
|
||||
@@ -8,6 +8,7 @@ import { getDriftService } from '../drift/client'
|
||||
import { closePosition } from '../drift/orders'
|
||||
import { getPythPriceMonitor, PriceUpdate } from '../pyth/price-monitor'
|
||||
import { getMergedConfig, TradingConfig } from '../../config/trading'
|
||||
import { updateTradeExit, updateTradeState, getOpenTrades } from '../database/trades'
|
||||
|
||||
export interface ActiveTrade {
|
||||
id: string
|
||||
@@ -46,7 +47,7 @@ export interface ActiveTrade {
|
||||
|
||||
export interface ExitResult {
|
||||
success: boolean
|
||||
reason: 'TP1' | 'TP2' | 'SL' | 'emergency' | 'manual' | 'error'
|
||||
reason: 'TP1' | 'TP2' | 'SL' | 'SOFT_SL' | 'HARD_SL' | 'emergency' | 'manual' | 'error'
|
||||
closePrice?: number
|
||||
closedSize?: number
|
||||
realizedPnL?: number
|
||||
@@ -58,12 +59,74 @@ export class PositionManager {
|
||||
private activeTrades: Map<string, ActiveTrade> = new Map()
|
||||
private config: TradingConfig
|
||||
private isMonitoring: boolean = false
|
||||
private initialized: boolean = false
|
||||
|
||||
constructor(config?: Partial<TradingConfig>) {
|
||||
this.config = getMergedConfig(config)
|
||||
console.log('✅ Position manager created')
|
||||
}
|
||||
|
||||
/**
|
||||
* Initialize and restore active trades from database
|
||||
*/
|
||||
async initialize(): Promise<void> {
|
||||
if (this.initialized) {
|
||||
return
|
||||
}
|
||||
|
||||
console.log('🔄 Restoring active trades from database...')
|
||||
|
||||
try {
|
||||
const openTrades = await getOpenTrades()
|
||||
|
||||
for (const dbTrade of openTrades) {
|
||||
// Extract Position Manager state from configSnapshot
|
||||
const pmState = (dbTrade.configSnapshot as any)?.positionManagerState
|
||||
|
||||
// Reconstruct ActiveTrade object
|
||||
const activeTrade: ActiveTrade = {
|
||||
id: dbTrade.id,
|
||||
positionId: dbTrade.positionId,
|
||||
symbol: dbTrade.symbol,
|
||||
direction: dbTrade.direction as 'long' | 'short',
|
||||
entryPrice: dbTrade.entryPrice,
|
||||
entryTime: dbTrade.entryTime.getTime(),
|
||||
positionSize: dbTrade.positionSizeUSD,
|
||||
leverage: dbTrade.leverage,
|
||||
stopLossPrice: pmState?.stopLossPrice ?? dbTrade.stopLossPrice,
|
||||
tp1Price: dbTrade.takeProfit1Price,
|
||||
tp2Price: dbTrade.takeProfit2Price,
|
||||
emergencyStopPrice: dbTrade.stopLossPrice * (dbTrade.direction === 'long' ? 0.98 : 1.02),
|
||||
currentSize: pmState?.currentSize ?? dbTrade.positionSizeUSD,
|
||||
tp1Hit: pmState?.tp1Hit ?? false,
|
||||
slMovedToBreakeven: pmState?.slMovedToBreakeven ?? false,
|
||||
slMovedToProfit: pmState?.slMovedToProfit ?? false,
|
||||
realizedPnL: pmState?.realizedPnL ?? 0,
|
||||
unrealizedPnL: pmState?.unrealizedPnL ?? 0,
|
||||
peakPnL: pmState?.peakPnL ?? 0,
|
||||
priceCheckCount: 0,
|
||||
lastPrice: pmState?.lastPrice ?? dbTrade.entryPrice,
|
||||
lastUpdateTime: Date.now(),
|
||||
}
|
||||
|
||||
this.activeTrades.set(activeTrade.id, activeTrade)
|
||||
console.log(`✅ Restored trade: ${activeTrade.symbol} ${activeTrade.direction} at $${activeTrade.entryPrice}`)
|
||||
}
|
||||
|
||||
if (this.activeTrades.size > 0) {
|
||||
console.log(`🎯 Restored ${this.activeTrades.size} active trades`)
|
||||
await this.startMonitoring()
|
||||
} else {
|
||||
console.log('✅ No active trades to restore')
|
||||
}
|
||||
|
||||
} catch (error) {
|
||||
console.error('❌ Failed to restore active trades:', error)
|
||||
}
|
||||
|
||||
this.initialized = true
|
||||
}
|
||||
|
||||
/**
|
||||
* Add a new trade to monitor
|
||||
*/
|
||||
@@ -72,6 +135,9 @@ export class PositionManager {
|
||||
|
||||
this.activeTrades.set(trade.id, trade)
|
||||
|
||||
// Save initial state to database
|
||||
await this.saveTradeState(trade)
|
||||
|
||||
console.log(`✅ Trade added. Active trades: ${this.activeTrades.size}`)
|
||||
|
||||
// Start monitoring if not already running
|
||||
@@ -238,17 +304,20 @@ export class PositionManager {
|
||||
console.log(`🎉 TP1 HIT: ${trade.symbol} at ${profitPercent.toFixed(2)}%`)
|
||||
await this.executeExit(trade, 50, 'TP1', currentPrice)
|
||||
|
||||
// Move SL to breakeven
|
||||
// Move SL to secure profit after TP1
|
||||
trade.tp1Hit = true
|
||||
trade.currentSize = trade.positionSize * 0.5
|
||||
trade.stopLossPrice = this.calculatePrice(
|
||||
trade.entryPrice,
|
||||
0.15, // +0.15% to cover fees
|
||||
0.35, // +0.35% to secure profit and avoid stop-out on retracement
|
||||
trade.direction
|
||||
)
|
||||
trade.slMovedToBreakeven = true
|
||||
|
||||
console.log(`🔒 SL moved to breakeven: ${trade.stopLossPrice.toFixed(4)}`)
|
||||
console.log(`🔒 SL moved to +0.35% (half of TP1): ${trade.stopLossPrice.toFixed(4)}`)
|
||||
|
||||
// Save state after TP1
|
||||
await this.saveTradeState(trade)
|
||||
return
|
||||
}
|
||||
|
||||
@@ -268,6 +337,9 @@ export class PositionManager {
|
||||
trade.slMovedToProfit = true
|
||||
|
||||
console.log(`🎯 SL moved to +${this.config.profitLockPercent}%: ${trade.stopLossPrice.toFixed(4)}`)
|
||||
|
||||
// Save state after profit lock
|
||||
await this.saveTradeState(trade)
|
||||
}
|
||||
|
||||
// 5. Take profit 2 (remaining 50%)
|
||||
@@ -305,8 +377,29 @@ export class PositionManager {
|
||||
if (percentToClose >= 100) {
|
||||
// Full close - remove from monitoring
|
||||
trade.realizedPnL += result.realizedPnL || 0
|
||||
this.removeTrade(trade.id)
|
||||
|
||||
// Save to database (only for valid exit reasons)
|
||||
if (reason !== 'error') {
|
||||
try {
|
||||
const holdTimeSeconds = Math.floor((Date.now() - trade.entryTime) / 1000)
|
||||
await updateTradeExit({
|
||||
positionId: trade.positionId,
|
||||
exitPrice: result.closePrice || currentPrice,
|
||||
exitReason: reason as 'TP1' | 'TP2' | 'SL' | 'SOFT_SL' | 'HARD_SL' | 'manual' | 'emergency',
|
||||
realizedPnL: trade.realizedPnL,
|
||||
exitOrderTx: result.transactionSignature || 'MANUAL_CLOSE',
|
||||
holdTimeSeconds,
|
||||
maxDrawdown: 0, // TODO: Track this
|
||||
maxGain: trade.peakPnL,
|
||||
})
|
||||
console.log('💾 Trade saved to database')
|
||||
} catch (dbError) {
|
||||
console.error('❌ Failed to save trade exit to database:', dbError)
|
||||
// Don't fail the close if database fails
|
||||
}
|
||||
}
|
||||
|
||||
this.removeTrade(trade.id)
|
||||
console.log(`✅ Position closed | P&L: $${trade.realizedPnL.toFixed(2)} | Reason: ${reason}`)
|
||||
} else {
|
||||
// Partial close (TP1)
|
||||
@@ -316,7 +409,6 @@ export class PositionManager {
|
||||
console.log(`✅ 50% closed | Realized: $${result.realizedPnL?.toFixed(2)} | Remaining: ${trade.currentSize}`)
|
||||
}
|
||||
|
||||
// TODO: Save to database
|
||||
// TODO: Send notification
|
||||
|
||||
} catch (error) {
|
||||
@@ -404,6 +496,29 @@ export class PositionManager {
|
||||
console.log('✅ All positions closed')
|
||||
}
|
||||
|
||||
/**
|
||||
* Save trade state to database (for persistence across restarts)
|
||||
*/
|
||||
private async saveTradeState(trade: ActiveTrade): Promise<void> {
|
||||
try {
|
||||
await updateTradeState({
|
||||
positionId: trade.positionId,
|
||||
currentSize: trade.currentSize,
|
||||
tp1Hit: trade.tp1Hit,
|
||||
slMovedToBreakeven: trade.slMovedToBreakeven,
|
||||
slMovedToProfit: trade.slMovedToProfit,
|
||||
stopLossPrice: trade.stopLossPrice,
|
||||
realizedPnL: trade.realizedPnL,
|
||||
unrealizedPnL: trade.unrealizedPnL,
|
||||
peakPnL: trade.peakPnL,
|
||||
lastPrice: trade.lastPrice,
|
||||
})
|
||||
} catch (error) {
|
||||
console.error('❌ Failed to save trade state:', error)
|
||||
// Don't throw - state save is non-critical
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get monitoring status
|
||||
*/
|
||||
@@ -426,10 +541,26 @@ export class PositionManager {
|
||||
|
||||
// Singleton instance
|
||||
let positionManagerInstance: PositionManager | null = null
|
||||
let initPromise: Promise<void> | null = null
|
||||
|
||||
export function getPositionManager(): PositionManager {
|
||||
if (!positionManagerInstance) {
|
||||
positionManagerInstance = new PositionManager()
|
||||
|
||||
// Initialize asynchronously (restore trades from database)
|
||||
if (!initPromise) {
|
||||
initPromise = positionManagerInstance.initialize().catch(error => {
|
||||
console.error('❌ Failed to initialize Position Manager:', error)
|
||||
})
|
||||
}
|
||||
}
|
||||
return positionManagerInstance
|
||||
}
|
||||
|
||||
export async function getInitializedPositionManager(): Promise<PositionManager> {
|
||||
const manager = getPositionManager()
|
||||
if (initPromise) {
|
||||
await initPromise
|
||||
}
|
||||
return manager
|
||||
}
|
||||
|
||||
171
n8n-daily-report.json
Normal file
171
n8n-daily-report.json
Normal file
@@ -0,0 +1,171 @@
|
||||
{
|
||||
"name": "Daily Trading Report",
|
||||
"nodes": [
|
||||
{
|
||||
"parameters": {
|
||||
"rule": {
|
||||
"interval": [
|
||||
{
|
||||
"triggerAtHour": 0,
|
||||
"triggerAtMinute": 5
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"id": "1a2b3c4d-5e6f-7a8b-9c0d-1e2f3a4b5c6d",
|
||||
"name": "Every Day at Midnight",
|
||||
"type": "n8n-nodes-base.scheduleTrigger",
|
||||
"typeVersion": 1.2,
|
||||
"position": [240, 300]
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "executeQuery",
|
||||
"query": "-- Get yesterday's trading activity\nSELECT \n COUNT(*) as total_trades,\n COUNT(CASE WHEN \"realizedPnL\" > 0 THEN 1 END) as winning_trades,\n COUNT(CASE WHEN \"realizedPnL\" < 0 THEN 1 END) as losing_trades,\n SUM(\"realizedPnL\") as total_pnl,\n AVG(\"realizedPnL\") as avg_pnl,\n MAX(\"realizedPnL\") as best_trade,\n MIN(\"realizedPnL\") as worst_trade,\n AVG(\"holdTimeSeconds\") / 60 as avg_hold_time_minutes\nFROM \"Trade\"\nWHERE status = 'closed'\n AND \"isTestTrade\" = false\n AND \"exitTime\" >= CURRENT_DATE - INTERVAL '1 day'\n AND \"exitTime\" < CURRENT_DATE;"
|
||||
},
|
||||
"id": "2b3c4d5e-6f7a-8b9c-0d1e-2f3a4b5c6d7e",
|
||||
"name": "Query Yesterday Stats",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [460, 300],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "executeQuery",
|
||||
"query": "-- Get breakdown by symbol\nSELECT \n symbol,\n COUNT(*) as trades,\n SUM(\"realizedPnL\") as pnl\nFROM \"Trade\"\nWHERE status = 'closed'\n AND \"isTestTrade\" = false\n AND \"exitTime\" >= CURRENT_DATE - INTERVAL '1 day'\n AND \"exitTime\" < CURRENT_DATE\nGROUP BY symbol\nORDER BY pnl DESC;"
|
||||
},
|
||||
"id": "3c4d5e6f-7a8b-9c0d-1e2f-3a4b5c6d7e8f",
|
||||
"name": "Query Symbol Breakdown",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [460, 500],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "insert",
|
||||
"schema": {
|
||||
"__rl": true,
|
||||
"value": "public",
|
||||
"mode": "list",
|
||||
"cachedResultName": "public"
|
||||
},
|
||||
"table": {
|
||||
"__rl": true,
|
||||
"value": "DailyStats",
|
||||
"mode": "list",
|
||||
"cachedResultName": "DailyStats"
|
||||
},
|
||||
"columns": {
|
||||
"mappingMode": "defineBelow",
|
||||
"value": {
|
||||
"date": "={{ $json.date }}",
|
||||
"tradesCount": "={{ $json.total_trades }}",
|
||||
"winningTrades": "={{ $json.winning_trades }}",
|
||||
"losingTrades": "={{ $json.losing_trades }}",
|
||||
"totalPnL": "={{ $json.total_pnl }}",
|
||||
"totalPnLPercent": "0",
|
||||
"winRate": "={{ $json.win_rate }}",
|
||||
"avgWin": "={{ $json.avg_win }}",
|
||||
"avgLoss": "={{ $json.avg_loss }}",
|
||||
"profitFactor": "={{ $json.profit_factor }}",
|
||||
"maxDrawdown": "0",
|
||||
"sharpeRatio": "0"
|
||||
}
|
||||
}
|
||||
},
|
||||
"id": "4d5e6f7a-8b9c-0d1e-2f3a-4b5c6d7e8f9a",
|
||||
"name": "Save Daily Stats",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [900, 300],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"jsCode": "const stats = $('Query Yesterday Stats').first().json;\nconst symbols = $('Query Symbol Breakdown').all();\n\nconst winRate = stats.total_trades > 0 ? (stats.winning_trades / stats.total_trades) * 100 : 0;\nconst avgWin = stats.winning_trades > 0 ? stats.total_pnl / stats.winning_trades : 0;\nconst avgLoss = stats.losing_trades > 0 ? Math.abs(stats.total_pnl / stats.losing_trades) : 0;\nconst profitFactor = avgLoss !== 0 ? avgWin / avgLoss : 0;\n\nconst yesterday = new Date();\nyesterday.setDate(yesterday.getDate() - 1);\nyesterday.setHours(0, 0, 0, 0);\n\nreturn [{\n json: {\n date: yesterday.toISOString(),\n total_trades: parseInt(stats.total_trades) || 0,\n winning_trades: parseInt(stats.winning_trades) || 0,\n losing_trades: parseInt(stats.losing_trades) || 0,\n total_pnl: parseFloat(stats.total_pnl) || 0,\n win_rate: winRate,\n avg_win: avgWin,\n avg_loss: avgLoss,\n profit_factor: profitFactor,\n symbols: symbols.map(s => s.json)\n }\n}];"
|
||||
},
|
||||
"id": "5e6f7a8b-9c0d-1e2f-3a4b-5c6d7e8f9a0b",
|
||||
"name": "Process Data",
|
||||
"type": "n8n-nodes-base.code",
|
||||
"typeVersion": 2,
|
||||
"position": [680, 300]
|
||||
}
|
||||
],
|
||||
"connections": {
|
||||
"Every Day at Midnight": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Query Yesterday Stats",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
},
|
||||
{
|
||||
"node": "Query Symbol Breakdown",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
},
|
||||
"Query Yesterday Stats": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Process Data",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
},
|
||||
"Query Symbol Breakdown": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Process Data",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
},
|
||||
"Process Data": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Save Daily Stats",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
}
|
||||
},
|
||||
"pinData": {},
|
||||
"settings": {
|
||||
"executionOrder": "v1"
|
||||
},
|
||||
"staticData": null,
|
||||
"tags": [],
|
||||
"triggerCount": 0,
|
||||
"updatedAt": "2025-10-27T00:00:00.000Z",
|
||||
"versionId": "1"
|
||||
}
|
||||
73
n8n-database-analytics.json
Normal file
73
n8n-database-analytics.json
Normal file
@@ -0,0 +1,73 @@
|
||||
{
|
||||
"name": "Trading Database Analytics",
|
||||
"nodes": [
|
||||
{
|
||||
"parameters": {},
|
||||
"id": "7c2dbef4-8f5f-4c0e-9f3c-4e5c5d8f2a1b",
|
||||
"name": "When clicking 'Test workflow'",
|
||||
"type": "n8n-nodes-base.manualTrigger",
|
||||
"typeVersion": 1,
|
||||
"position": [240, 300]
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "executeQuery",
|
||||
"query": "-- Get all closed trades with performance metrics\nSELECT \n id,\n symbol,\n direction,\n \"entryPrice\",\n \"exitPrice\",\n \"positionSizeUSD\",\n leverage,\n \"realizedPnL\",\n \"realizedPnLPercent\",\n \"holdTimeSeconds\",\n \"exitReason\",\n \"entryTime\",\n \"exitTime\",\n \"isTestTrade\",\n CASE \n WHEN \"realizedPnL\" > 0 THEN 'WIN'\n WHEN \"realizedPnL\" < 0 THEN 'LOSS'\n ELSE 'BREAKEVEN'\n END as trade_result\nFROM \"Trade\"\nWHERE status = 'closed'\n AND \"isTestTrade\" = false\nORDER BY \"exitTime\" DESC\nLIMIT 100;"
|
||||
},
|
||||
"id": "3f9c1d7b-2e4a-4c8f-9b1e-6d8e5c3f2a4b",
|
||||
"name": "Query Closed Trades",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [460, 300],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"jsCode": "// Calculate trading statistics from closed trades\nconst trades = $input.all();\n\nif (trades.length === 0) {\n return [{\n json: {\n message: 'No closed trades found',\n totalTrades: 0\n }\n }];\n}\n\nconst wins = trades.filter(t => t.json.trade_result === 'WIN');\nconst losses = trades.filter(t => t.json.trade_result === 'LOSS');\n\nconst totalPnL = trades.reduce((sum, t) => sum + parseFloat(t.json.realizedPnL || 0), 0);\nconst avgWin = wins.length > 0 ? wins.reduce((sum, t) => sum + parseFloat(t.json.realizedPnL), 0) / wins.length : 0;\nconst avgLoss = losses.length > 0 ? losses.reduce((sum, t) => sum + parseFloat(t.json.realizedPnL), 0) / losses.length : 0;\nconst winRate = (wins.length / trades.length) * 100;\nconst profitFactor = avgLoss !== 0 ? Math.abs(avgWin / avgLoss) : 0;\n\n// Calculate average hold time\nconst avgHoldTime = trades.reduce((sum, t) => sum + parseInt(t.json.holdTimeSeconds || 0), 0) / trades.length;\n\n// Group by symbol\nconst bySymbol = {};\ntrades.forEach(t => {\n const symbol = t.json.symbol;\n if (!bySymbol[symbol]) {\n bySymbol[symbol] = { trades: 0, wins: 0, pnl: 0 };\n }\n bySymbol[symbol].trades++;\n if (t.json.trade_result === 'WIN') bySymbol[symbol].wins++;\n bySymbol[symbol].pnl += parseFloat(t.json.realizedPnL || 0);\n});\n\n// Group by direction\nconst longs = trades.filter(t => t.json.direction === 'long');\nconst shorts = trades.filter(t => t.json.direction === 'short');\n\nconst longWins = longs.filter(t => t.json.trade_result === 'WIN').length;\nconst shortWins = shorts.filter(t => t.json.trade_result === 'WIN').length;\n\n// Group by exit reason\nconst exitReasons = {};\ntrades.forEach(t => {\n const reason = t.json.exitReason || 'unknown';\n if (!exitReasons[reason]) {\n exitReasons[reason] = { count: 0, pnl: 0 };\n }\n exitReasons[reason].count++;\n exitReasons[reason].pnl += parseFloat(t.json.realizedPnL || 0);\n});\n\nreturn [{\n json: {\n summary: {\n totalTrades: trades.length,\n winningTrades: wins.length,\n losingTrades: losses.length,\n winRate: winRate.toFixed(2) + '%',\n totalPnL: '$' + totalPnL.toFixed(2),\n avgWin: '$' + avgWin.toFixed(2),\n avgLoss: '$' + avgLoss.toFixed(2),\n profitFactor: profitFactor.toFixed(2),\n avgHoldTimeMinutes: (avgHoldTime / 60).toFixed(1)\n },\n bySymbol,\n byDirection: {\n long: {\n total: longs.length,\n wins: longWins,\n winRate: longs.length > 0 ? ((longWins / longs.length) * 100).toFixed(2) + '%' : '0%'\n },\n short: {\n total: shorts.length,\n wins: shortWins,\n winRate: shorts.length > 0 ? ((shortWins / shorts.length) * 100).toFixed(2) + '%' : '0%'\n }\n },\n exitReasons,\n timestamp: new Date().toISOString()\n }\n}];"
|
||||
},
|
||||
"id": "8a3b4c5d-6e7f-4a8b-9c0d-1e2f3a4b5c6d",
|
||||
"name": "Calculate Statistics",
|
||||
"type": "n8n-nodes-base.code",
|
||||
"typeVersion": 2,
|
||||
"position": [680, 300]
|
||||
}
|
||||
],
|
||||
"connections": {
|
||||
"When clicking 'Test workflow'": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Query Closed Trades",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
},
|
||||
"Query Closed Trades": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Calculate Statistics",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
}
|
||||
},
|
||||
"pinData": {},
|
||||
"settings": {
|
||||
"executionOrder": "v1"
|
||||
},
|
||||
"staticData": null,
|
||||
"tags": [],
|
||||
"triggerCount": 0,
|
||||
"updatedAt": "2025-10-27T00:00:00.000Z",
|
||||
"versionId": "1"
|
||||
}
|
||||
139
n8n-pattern-analysis.json
Normal file
139
n8n-pattern-analysis.json
Normal file
@@ -0,0 +1,139 @@
|
||||
{
|
||||
"name": "Pattern Analysis - Win Rate by Hour",
|
||||
"nodes": [
|
||||
{
|
||||
"parameters": {},
|
||||
"id": "1a2b3c4d-5e6f-7a8b-9c0d-1e2f3a4b5c6d",
|
||||
"name": "Manual Trigger",
|
||||
"type": "n8n-nodes-base.manualTrigger",
|
||||
"typeVersion": 1,
|
||||
"position": [240, 300]
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "executeQuery",
|
||||
"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;"
|
||||
},
|
||||
"id": "2b3c4d5e-6f7a-8b9c-0d1e-2f3a4b5c6d7e",
|
||||
"name": "Query Hourly Performance",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [460, 300],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "executeQuery",
|
||||
"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;"
|
||||
},
|
||||
"id": "3c4d5e6f-7a8b-9c0d-1e2f-3a4b5c6d7e8f",
|
||||
"name": "Query Daily Performance",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [460, 500],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "executeQuery",
|
||||
"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;"
|
||||
},
|
||||
"id": "4d5e6f7a-8b9c-0d1e-2f3a-4b5c6d7e8f9a",
|
||||
"name": "Query Hold Time Analysis",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [460, 700],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"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 }];"
|
||||
},
|
||||
"id": "5e6f7a8b-9c0d-1e2f-3a4b-5c6d7e8f9a0b",
|
||||
"name": "Generate Insights",
|
||||
"type": "n8n-nodes-base.code",
|
||||
"typeVersion": 2,
|
||||
"position": [680, 300]
|
||||
}
|
||||
],
|
||||
"connections": {
|
||||
"Manual Trigger": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Query Hourly Performance",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
},
|
||||
{
|
||||
"node": "Query Daily Performance",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
},
|
||||
{
|
||||
"node": "Query Hold Time Analysis",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
},
|
||||
"Query Hourly Performance": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Generate Insights",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
},
|
||||
"Query Daily Performance": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Generate Insights",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
},
|
||||
"Query Hold Time Analysis": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Generate Insights",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
}
|
||||
},
|
||||
"pinData": {},
|
||||
"settings": {
|
||||
"executionOrder": "v1"
|
||||
},
|
||||
"staticData": null,
|
||||
"tags": [],
|
||||
"triggerCount": 0,
|
||||
"updatedAt": "2025-10-27T00:00:00.000Z",
|
||||
"versionId": "1"
|
||||
}
|
||||
139
n8n-stop-loss-analysis.json
Normal file
139
n8n-stop-loss-analysis.json
Normal file
@@ -0,0 +1,139 @@
|
||||
{
|
||||
"name": "Stop Loss Analysis - Which Stops Get Hit",
|
||||
"nodes": [
|
||||
{
|
||||
"parameters": {},
|
||||
"id": "1a2b3c4d-5e6f-7a8b-9c0d-1e2f3a4b5c6d",
|
||||
"name": "Manual Trigger",
|
||||
"type": "n8n-nodes-base.manualTrigger",
|
||||
"typeVersion": 1,
|
||||
"position": [240, 300]
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "executeQuery",
|
||||
"query": "-- Exit reason breakdown\nSELECT \n \"exitReason\",\n COUNT(*) as count,\n ROUND(COUNT(*)::numeric / (SELECT COUNT(*) FROM \"Trade\" WHERE status = 'closed' AND \"isTestTrade\" = false) * 100, 2) as percentage,\n ROUND(AVG(\"realizedPnL\")::numeric, 4) as avg_pnl,\n ROUND(SUM(\"realizedPnL\")::numeric, 2) as total_pnl,\n ROUND(AVG(\"holdTimeSeconds\")::numeric / 60, 1) as avg_hold_minutes\nFROM \"Trade\"\nWHERE status = 'closed'\n AND \"isTestTrade\" = false\n AND \"entryTime\" >= NOW() - INTERVAL '30 days'\nGROUP BY \"exitReason\"\nORDER BY count DESC;"
|
||||
},
|
||||
"id": "2b3c4d5e-6f7a-8b9c-0d1e-2f3a4b5c6d7e",
|
||||
"name": "Query Exit Reasons",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [460, 300],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "executeQuery",
|
||||
"query": "-- Stop loss effectiveness by distance\nSELECT \n CASE \n WHEN ABS((\"stopLossPrice\" - \"entryPrice\") / \"entryPrice\" * 100) < 0.5 THEN 'Very Tight (< 0.5%)'\n WHEN ABS((\"stopLossPrice\" - \"entryPrice\") / \"entryPrice\" * 100) < 1.0 THEN 'Tight (0.5-1%)'\n WHEN ABS((\"stopLossPrice\" - \"entryPrice\") / \"entryPrice\" * 100) < 1.5 THEN 'Normal (1-1.5%)'\n WHEN ABS((\"stopLossPrice\" - \"entryPrice\") / \"entryPrice\" * 100) < 2.0 THEN 'Wide (1.5-2%)'\n ELSE 'Very Wide (> 2%)'\n END as sl_distance,\n COUNT(*) as total_trades,\n COUNT(CASE WHEN \"exitReason\" LIKE '%stop%' THEN 1 END) as stopped_out,\n ROUND(COUNT(CASE WHEN \"exitReason\" LIKE '%stop%' THEN 1 END)::numeric / NULLIF(COUNT(*), 0) * 100, 2) as stop_hit_rate,\n ROUND(AVG(\"realizedPnL\")::numeric, 4) as avg_pnl\nFROM \"Trade\"\nWHERE status = 'closed'\n AND \"isTestTrade\" = false\n AND \"stopLossPrice\" IS NOT NULL\n AND \"entryPrice\" > 0\n AND \"entryTime\" >= NOW() - INTERVAL '30 days'\nGROUP BY \n CASE \n WHEN ABS((\"stopLossPrice\" - \"entryPrice\") / \"entryPrice\" * 100) < 0.5 THEN 'Very Tight (< 0.5%)'\n WHEN ABS((\"stopLossPrice\" - \"entryPrice\") / \"entryPrice\" * 100) < 1.0 THEN 'Tight (0.5-1%)'\n WHEN ABS((\"stopLossPrice\" - \"entryPrice\") / \"entryPrice\" * 100) < 1.5 THEN 'Normal (1-1.5%)'\n WHEN ABS((\"stopLossPrice\" - \"entryPrice\") / \"entryPrice\" * 100) < 2.0 THEN 'Wide (1.5-2%)'\n ELSE 'Very Wide (> 2%)'\n END\nORDER BY \n CASE \n WHEN sl_distance = 'Very Tight (< 0.5%)' THEN 1\n WHEN sl_distance = 'Tight (0.5-1%)' THEN 2\n WHEN sl_distance = 'Normal (1-1.5%)' THEN 3\n WHEN sl_distance = 'Wide (1.5-2%)' THEN 4\n ELSE 5\n END;"
|
||||
},
|
||||
"id": "3c4d5e6f-7a8b-9c0d-1e2f-3a4b5c6d7e8f",
|
||||
"name": "Query Stop Distance Analysis",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [460, 500],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"operation": "executeQuery",
|
||||
"query": "-- Trades that got stopped out vs those that hit targets\nSELECT \n direction,\n symbol,\n COUNT(CASE WHEN \"exitReason\" LIKE '%stop%' THEN 1 END) as stopped_out,\n COUNT(CASE WHEN \"exitReason\" LIKE '%target%' OR \"exitReason\" LIKE '%TP%' THEN 1 END) as hit_targets,\n COUNT(CASE WHEN \"exitReason\" LIKE '%manual%' THEN 1 END) as manual_exits,\n ROUND(AVG(CASE WHEN \"exitReason\" LIKE '%stop%' THEN \"realizedPnL\" END)::numeric, 4) as avg_stop_loss,\n ROUND(AVG(CASE WHEN \"exitReason\" LIKE '%target%' OR \"exitReason\" LIKE '%TP%' THEN \"realizedPnL\" END)::numeric, 4) as avg_target_win\nFROM \"Trade\"\nWHERE status = 'closed'\n AND \"isTestTrade\" = false\n AND \"entryTime\" >= NOW() - INTERVAL '30 days'\nGROUP BY direction, symbol\nORDER BY stopped_out DESC;"
|
||||
},
|
||||
"id": "4d5e6f7a-8b9c-0d1e-2f3a-4b5c6d7e8f9a",
|
||||
"name": "Query Stop vs Target by Symbol",
|
||||
"type": "n8n-nodes-base.postgres",
|
||||
"typeVersion": 2.4,
|
||||
"position": [460, 700],
|
||||
"credentials": {
|
||||
"postgres": {
|
||||
"id": "1",
|
||||
"name": "Trading Bot Database"
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
"parameters": {
|
||||
"jsCode": "const exitReasons = $('Query Exit Reasons').all().map(item => item.json);\nconst stopDistances = $('Query Stop Distance Analysis').all().map(item => item.json);\nconst symbolBreakdown = $('Query Stop vs Target by Symbol').all().map(item => item.json);\n\n// Calculate stop loss hit rate\nconst stopLossExits = exitReasons.filter(r => r.exitReason && r.exitReason.toLowerCase().includes('stop'));\nconst totalStopLosses = stopLossExits.reduce((sum, r) => sum + parseInt(r.count), 0);\nconst totalTrades = exitReasons.reduce((sum, r) => sum + parseInt(r.count), 0);\nconst stopHitRate = totalTrades > 0 ? (totalStopLosses / totalTrades * 100).toFixed(2) : 0;\n\n// Find optimal stop distance\nconst sortedByPnL = [...stopDistances].sort((a, b) => parseFloat(b.avg_pnl) - parseFloat(a.avg_pnl));\nconst optimalDistance = sortedByPnL[0];\nconst worstDistance = sortedByPnL[sortedByPnL.length - 1];\n\n// Calculate profit factor (avg win / avg loss)\nconst avgStopLoss = exitReasons\n .filter(r => r.exitReason && r.exitReason.toLowerCase().includes('stop'))\n .reduce((sum, r) => sum + parseFloat(r.avg_pnl) * parseInt(r.count), 0) / totalStopLosses;\n\nconst targetExits = exitReasons.filter(r => \n r.exitReason && (r.exitReason.toLowerCase().includes('target') || r.exitReason.toLowerCase().includes('tp'))\n);\nconst totalTargets = targetExits.reduce((sum, r) => sum + parseInt(r.count), 0);\nconst avgTarget = targetExits.reduce((sum, r) => sum + parseFloat(r.avg_pnl) * parseInt(r.count), 0) / totalTargets;\n\nconst insights = {\n summary: {\n stopHitRate: `${stopHitRate}%`,\n totalStopLosses,\n avgStopLoss: `$${avgStopLoss.toFixed(4)}`,\n avgTargetWin: `$${avgTarget.toFixed(4)}`,\n profitFactor: avgStopLoss !== 0 ? (Math.abs(avgTarget / avgStopLoss)).toFixed(2) : 'N/A'\n },\n optimalStopDistance: {\n distance: optimalDistance?.sl_distance || 'N/A',\n avgPnL: optimalDistance ? `$${optimalDistance.avg_pnl}` : 'N/A',\n stopHitRate: optimalDistance ? `${optimalDistance.stop_hit_rate}%` : 'N/A',\n recommendation: optimalDistance ? `Use ${optimalDistance.sl_distance} stop losses` : 'Need more data'\n },\n worstStopDistance: {\n distance: worstDistance?.sl_distance || 'N/A',\n avgPnL: worstDistance ? `$${worstDistance.avg_pnl}` : 'N/A',\n stopHitRate: worstDistance ? `${worstDistance.stop_hit_rate}%` : 'N/A'\n },\n recommendations: [\n stopHitRate > 50 ? '⚠️ High stop hit rate - consider wider stops or better entries' : '✅ Stop hit rate is acceptable',\n optimalDistance && worstDistance ? `💡 ${optimalDistance.sl_distance} performs ${((parseFloat(optimalDistance.avg_pnl) - parseFloat(worstDistance.avg_pnl)) / Math.abs(parseFloat(worstDistance.avg_pnl)) * 100).toFixed(1)}% better than ${worstDistance.sl_distance}` : '',\n Math.abs(avgStopLoss) > Math.abs(avgTarget) ? '⚠️ Average losses exceed average wins - adjust risk/reward' : '✅ Risk/reward ratio is positive'\n ].filter(Boolean),\n rawData: {\n exitReasons,\n stopDistances,\n symbolBreakdown\n }\n};\n\nreturn [{ json: insights }];"
|
||||
},
|
||||
"id": "5e6f7a8b-9c0d-1e2f-3a4b-5c6d7e8f9a0b",
|
||||
"name": "Analyze Stop Effectiveness",
|
||||
"type": "n8n-nodes-base.code",
|
||||
"typeVersion": 2,
|
||||
"position": [680, 300]
|
||||
}
|
||||
],
|
||||
"connections": {
|
||||
"Manual Trigger": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Query Exit Reasons",
|
||||
"type": "main",
|
||||
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|
||||
},
|
||||
{
|
||||
"node": "Query Stop Distance Analysis",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
},
|
||||
{
|
||||
"node": "Query Stop vs Target by Symbol",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
},
|
||||
"Query Exit Reasons": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Analyze Stop Effectiveness",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
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|
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]
|
||||
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|
||||
},
|
||||
"Query Stop Distance Analysis": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Analyze Stop Effectiveness",
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||||
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|
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}
|
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]
|
||||
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|
||||
},
|
||||
"Query Stop vs Target by Symbol": {
|
||||
"main": [
|
||||
[
|
||||
{
|
||||
"node": "Analyze Stop Effectiveness",
|
||||
"type": "main",
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
]
|
||||
}
|
||||
},
|
||||
"pinData": {},
|
||||
"settings": {
|
||||
"executionOrder": "v1"
|
||||
},
|
||||
"staticData": null,
|
||||
"tags": [],
|
||||
"triggerCount": 0,
|
||||
"updatedAt": "2025-10-27T00:00:00.000Z",
|
||||
"versionId": "1"
|
||||
}
|
||||
Reference in New Issue
Block a user