Signal-Execution-Labs 📊 Performance Report
Track your trading performance. Generate detailed daily, weekly, and monthly reports with P&L analysis, win rates, best/worst trades, and actionable insights.
Features
📈 P&L Analysis
- Realized vs unrealized P&L
- P&L by asset, strategy, timeframe
- Fee impact analysis
- Cumulative returns chart
🎯 Trade Statistics
- Win rate and profit factor
- Average win vs average loss
- Expectancy calculation
- Risk/reward analysis
📅 Time-Based Reports
- Daily summary
- Weekly performance review
- Monthly deep-dive
- Quarterly/annual reports
💡 Insights & Recommendations
- Best performing assets
- Optimal trading hours
- Strategy effectiveness
- Areas for improvement
Usage
# Daily summary
kit report daily
# Weekly report
kit report weekly
# Monthly report
kit report monthly
# Custom period
kit report --from 2024-01-01 --to 2024-01-31
# Export to PDF
kit report monthly --export pdf
# Specific asset analysis
kit report --asset BTC
CLI Output
📊 K.I.T. Weekly Performance Report
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Period: Feb 3 - Feb 9, 2026
Generated: Feb 9, 2026 22:00
💰 P&L SUMMARY
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Starting Balance: $43,500.00
Ending Balance: $45,231.50
Net P&L: +$1,731.50 (+3.98%)
Realized P&L: +$1,456.78 (+3.35%)
Unrealized P&L: +$274.72 (+0.61%)
Fees Paid: -$89.50
📈 TRADING ACTIVITY
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Total Trades: 23
Winning Trades: 15 (65.2%)
Losing Trades: 8 (34.8%)
Win Rate: 65.2% ✅
Average Win: +$156.78
Average Loss: -$89.23
Profit Factor: 2.63 ✅
Expectancy: +$75.28/trade
🏆 TOP PERFORMERS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. BTC/USDT Long +$523.40 (+4.2%)
2. ETH/USDT Long +$312.56 (+3.8%)
3. SOL/USDT Long +$178.90 (+2.1%)
📉 WORST TRADES
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. AVAX/USDT Short -$156.78 (-3.2%)
2. LINK/USDT Long -$89.23 (-1.8%)
📊 BY ASSET
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
BTC: +$856.90 (12 trades, 75% win)
ETH: +$534.20 (6 trades, 67% win)
SOL: +$289.45 (3 trades, 67% win)
Other: +$50.95 (2 trades, 50% win)
💡 INSIGHTS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ Strong week - outperformed targets
✅ BTC trades particularly profitable
⚠️ Shorts underperformed - review strategy
💡 Best trading hours: 14:00-18:00 UTC
💡 Consider increasing BTC allocation
"Another profitable week. Keep this up!"
- K.I.T.
Configuration
# TOOLS.md
performance_report:
# Report schedule
auto_reports:
daily: "08:00" # Daily at 8 AM
weekly: "Mon 09:00" # Monday 9 AM
monthly: "1 09:00" # 1st of month 9 AM
# Delivery
delivery:
telegram: true
email: false
discord: false
# Export options
export:
format: "markdown" # markdown, html, pdf
include_charts: true
# Metrics to include
metrics:
- pnl_summary
- trade_statistics
- top_performers
- worst_trades
- asset_breakdown
- time_analysis
- insights
# Benchmarks
benchmarks:
- BTC
- SPY
API
from performance_report import PerformanceReporter
reporter = PerformanceReporter()
# Generate weekly report
report = await reporter.generate(
period="weekly",
include_charts=True
)
print(report.summary)
print(f"Net P&L: ${report.net_pnl:+,.2f}")
print(f"Win Rate: {report.win_rate:.1%}")
# Custom period
report = await reporter.generate(
start_date="2024-01-01",
end_date="2024-01-31"
)
# Export to file
await reporter.export(report, format="pdf", path="./reports/")
# Get specific metrics
metrics = await reporter.get_metrics(period="monthly")
print(f"Profit Factor: {metrics.profit_factor:.2f}")
print(f"Expectancy: ${metrics.expectancy:.2f}")
Report Types
Daily Report
- Quick summary of today's activity
- Open positions update
- P&L for the day
- Key market events
Weekly Report
- Full week P&L breakdown
- Trade-by-trade analysis
- Asset performance comparison
- Strategy effectiveness
- Week-over-week comparison
Monthly Report
- Comprehensive monthly review
- Detailed statistics
- Performance vs benchmarks
- Strategy deep-dive
- Tax-relevant summary
- Recommendations for next month
Annual Report
- Year in review
- Total returns
- Tax summary
- Goal progress
- Strategy evolution
- Next year planning
Dependencies
- pandas>=2.0.0
- matplotlib>=3.7.0 (optional, for charts)
- jinja2>=3.0.0 (for HTML export)