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." 📔