Trade Journal 📔
Automatisches Trading-Tagebuch. Dokumentiert jeden Trade mit Screenshots, Notizen und Performance-Statistiken.
Trigger Keywords
- journal, tagebuch, trade journal
- log trade, trade eintragen
- meine trades, trade history
- performance, statistiken
- review trades, analyse
Features
- Automatisches Logging: Jeder Trade wird automatisch erfasst
- Screenshots: Chart-Screenshots beim Entry/Exit
- Notizen: Begründung für jeden Trade
- Statistiken: Win Rate, Profit Factor, Drawdown
- Export: CSV, Excel, PDF Reports
- Tags: Kategorisiere Trades (Breakout, Reversal, News, etc.)
Beispiele
"K.I.T., zeige meine Trades von heute"
"Trade Journal für letzte Woche"
"Was war mein bester Trade diesen Monat?"
"Analysiere meine Performance bei EURUSD"
"Füge Notiz hinzu: Trade #123 - Zu früh eingestiegen"
Trade Entry Format
{
"id": "T2026020901",
"symbol": "EURUSD",
"direction": "buy",
"entry_time": "2026-02-09T14:30:00Z",
"entry_price": 1.0850,
"exit_time": "2026-02-09T16:45:00Z",
"exit_price": 1.0892,
"lot_size": 0.1,
"pips": 42,
"profit": 42.00,
"setup": "London Breakout",
"tags": ["breakout", "trend-following"],
"notes": "Clean break above resistance",
"screenshot": "screenshots/T2026020901.png"
}
API
from skills.trade_journal import TradeJournal, Trade
# Journal initialisieren
journal = TradeJournal("./journal_data")
# Trade hinzufügen
trade = Trade(
symbol="EURUSD",
direction="buy",
entry_price=1.0850,
exit_price=1.0892,
lot_size=0.1,
setup="London Breakout",
notes="Clean break above resistance"
)
journal.add_trade(trade)
# Statistiken abrufen
stats = journal.get_statistics(period="month")
print(f"Win Rate: {stats['win_rate']}%")
print(f"Profit Factor: {stats['profit_factor']}")
print(f"Total P&L: ${stats['total_profit']}")
# Trades filtern
eurusd_trades = journal.get_trades(symbol="EURUSD", period="week")
Statistiken
| Metrik | Beschreibung |
|---|---|
| Win Rate | % gewinnende Trades |
| Profit Factor | Gross Profit / Gross Loss |
| Average Win | Durchschnittlicher Gewinn |
| Average Loss | Durchschnittlicher Verlust |
| Largest Win | Größter Gewinn |
| Largest Loss | Größter Verlust |
| Max Drawdown | Maximaler Rückgang |
| Expectancy | Erwartungswert pro Trade |
| R-Multiple | Vielfaches des Risikos |
Report Beispiel
📔 K.I.T. TRADE JOURNAL
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📅 Periode: 01.02.2026 - 09.02.2026
📊 OVERVIEW
Total Trades: 42
Winning Trades: 28 (66.7%)
Losing Trades: 14 (33.3%)
💰 PERFORMANCE
Total Profit: $1,234.50
Profit Factor: 2.35
Average Win: $67.50
Average Loss: -$32.10
📈 BEST PERFORMERS
1. EURUSD +$456.00 (12 trades)
2. GBPJPY +$321.00 (8 trades)
3. XAUUSD +$234.00 (6 trades)
🏷️ TOP SETUPS
• London Breakout: 78% win rate
• Trend Pullback: 71% win rate
• News Reversal: 45% win rate
💡 INSIGHTS
• Best day: Tuesday (75% win rate)
• Best time: 14:00-16:00 UTC
• Avoid: Friday afternoon trades
Konfiguration
trade_journal:
data_path: "./journal"
auto_screenshot: true
screenshot_quality: 80
backup_enabled: true
export_format: "csv"
Integration mit MT5
# Automatisches Logging aktivieren
from skills.trade_journal import TradeJournal
from skills.metatrader import MT5Orders
journal = TradeJournal()
orders = MT5Orders()
# Hook für automatisches Logging
orders.on_trade_close(journal.add_trade_from_position)
K.I.T. - "The best traders are students of their own trades." 📔