portfolio-analysis-agent
Skill3 starsChanged 12 months agoMITView on GitHub
Version: 1.0.0 Category: Financial Analysis / Portfolio Management Author: Claude Code Last Updated: November 22, 2025 Comprehensive portfolio analysis system integrating historical trade analysis, forward projections, tax planning, and risk assessment into a unified workflow. Workflow: 1. Load IB CSV statement 2. Calculate trading metrics 3. Identify trading edge 4. Run 3-year projections 5. Analyze risk 6. Calculate tax obligations 7. Generate comprehensive report Output: - portfolio_analysis_YYYYMMDD.md - Full report - portfolio_dashboard_YYYYMMDD.json - Dashboard data - portfolio_trades.csv - Trade-by-trade export
In this repository11 other files it gives its agents.
- forecasting-agentSkill
- kymera-integratorSkill
- kymera-mr-optimizerSkill
- kymera-portfolio-checkerSkill
- kymera-risk-monitorSkill
- kymera-tax-optimizerSkill
- paper-reviewerSkill
- SKILL.mdSkill
- system-health-checkSkill
- trading-analysisSkill
- youtube-transcriberSkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
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Very specific
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- Common
- Distinctive
- Very specific
- Distinctive: line 408
Solution: Verify IB statement format.
- Distinctive: line 411
Solution: Ensure sufficient trade history (10+ trades).
- Distinctive: line 422
Check CSV format (most common issue)
- Distinctive: line 423
Verify config YAML structure
- Distinctive: line 425
Test with smaller datasets first
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Portfolio Analysis Agent
Version: 1.0.0 Category: Financial Analysis / Portfolio Management Author: Claude Code Last Updated: November 22, 2025
Overview
Comprehensive portfolio analysis system integrating historical trade analysis, forward projections, tax planning, and risk assessment into a unified workflow.
Features
1. Integrated Analysis
- Historical trade performance
- Forward projections (3-5 years)
- Tax obligation forecasting
- Risk metric calculation
- Edge identification
- Complete portfolio dashboard
2. Trading Analysis
- Load Interactive Brokers CSV statements
- Calculate win rate, average returns, profit factor
- Time-of-day edge analysis
- Symbol-level performance
- Position sizing audit
3. Forward Projections
- Multi-year portfolio growth forecasts
- Scenario analysis (conservative/baseline/aggressive)
- Quarterly tax extraction modeling
- Monthly and quarterly breakdowns
4. Tax Planning
- Quarterly tax obligation calculations
- Federal + state tax breakdown
- Multi-state comparisons (NY vs FL/TX)
- Payment schedule generation
- Tax reserve tracking
5. Risk Analysis
- Maximum drawdown calculations
- Sharpe ratio approximations
- Volatility metrics
- Position sizing recommendations
- Stop-loss impact analysis
6. Dashboard & Reporting
- Comprehensive portfolio dashboard (JSON)
- Markdown and LaTeX reports
- CSV exports of all data
- Google Drive integration
- Performance tracking over time
Usage
Complete Portfolio Analysis
/analyze-portfolio <path-to-csv>Workflow:
- Load IB CSV statement
- Calculate trading metrics
- Identify trading edge
- Run 3-year projections
- Analyze risk
- Calculate tax obligations
- Generate comprehensive report
Output:
portfolio_analysis_YYYYMMDD.md- Full reportportfolio_dashboard_YYYYMMDD.json- Dashboard dataportfolio_trades.csv- Trade-by-trade export
Generate PDF Report
/portfolio-report --format pdfOutput:
- Professional LaTeX PDF report (15+ pages)
- Executive summary
- Trade analysis
- Edge identification
- Forward projections
- Tax planning
- Risk assessment
- Recommendations
Track Performance
/portfolio-track --month 11What It Does:
- Compare actual vs projected performance
- Calculate variance
- Identify deviations
- Update baseline assumptions
- Recalibrate projections
Edge Analysis Only
/portfolio-edge-analysisOutput:
- Time-of-day performance breakdown
- Symbol-level profitability
- Intraday vs swing trade comparison
- Best/worst time windows
- Repeatable pattern identification
Configuration
Uses PORTFOLIO_PARAMETERS_COMPLETE.yaml:
trading:
return_per_trade:
all_time_avg: 3.58
win_rate:
actual: 90.0
trade_frequency:
trades_per_month:
baseline: 18.5
account:
initial_capital: 2000
monthly_deposits: 500
tax:
quarterly_extraction_pct: 37.0Complete Workflow
Step 1: Load Trading Data
agent.load_trading_csv('U21858510_20250101_20251120.csv')Parses:
- Closed positions
- Entry/exit prices and dates
- Commissions
- Realized P&L
Step 2: Calculate Metrics
metrics = agent.calculate_metrics()Calculates:
- Win rate (90%)
- Average return per trade (3.58%)
- Trades per month (18.5)
- Gross profits/losses
- Profit factor
Step 3: Identify Edge
edge = agent.identify_edge()Identifies:
- Best time windows (04:00-05:00 ET, 11:00-12:00 ET)
- Intraday vs swing performance
- Repeatable patterns
- Symbol-level edges
Step 4: Run Projections
projections = agent.run_projections(years=3)Projects:
- Year 1: $5.2M
- Year 2: $50B
- Year 3: $3.2T
Step 5: Analyze Risk
risk = agent.analyze_risk()Calculates:
- Max drawdown: -8.2%
- Sharpe ratio: ~2.5
- Position sizing risk
- Stop-loss impact
Step 6: Calculate Taxes
taxes = agent.calculate_taxes(state='NY')Calculates:
- Federal: 37%
- NY State: 10.75%
- Total: 47.75%
- Quarterly payments
Step 7: Generate Dashboard
dashboard = agent.generate_dashboard()Includes:
- All metrics
- Edge analysis
- Projections
- Risk metrics
- Tax obligations
Step 8: Generate Report
report_path = agent.generate_report(format='markdown')Generates:
- Executive summary
- Complete analysis
- Recommendations
- Action items
Dashboard Structure
{
"generated_at": "2025-11-22T10:30:00",
"account_info": {
"account": "U21858510",
"entity": "Kymera Systems LLC"
},
"metrics": {
"total_trades": 10,
"win_rate": 0.90,
"avg_return_pct": 0.0358,
"total_pnl": 283.94
},
"edge_analysis": {
"edge_identified": true,
"best_window": "premarket_0400_0500",
"best_window_stats": {
"trades": 2,
"win_rate": 100.0,
"avg_pnl": 79.49
}
},
"projections": {
"years": 3,
"final_balance": 3200000000000
},
"risk_metrics": {
"max_drawdown_pct": -8.2,
"sharpe_ratio": 2.5
},
"tax_analysis": {
"state": "FL",
"total_tax": 1184000000000
}
}Report Sections
1. Executive Summary
- Account overview
- Performance highlights
- Key findings
- Critical actions
2. Trading Analysis
- Win rate and profit factor
- Average returns
- Trade frequency
- Commission analysis
3. Edge Identification
- Time-of-day performance
- Symbol-level analysis
- Intraday vs swing comparison
- Repeatability assessment
4. Forward Projections
- 3-year baseline scenario
- Alternative scenarios
- Sensitivity analysis
- Milestone tracking
5. Risk Assessment
- Drawdown analysis
- Volatility metrics
- Position sizing review
- Stop-loss recommendations
6. Tax Planning
- Quarterly obligations
- Federal + state breakdown
- Payment schedule
- Reserve account strategy
7. Recommendations
- Immediate actions
- Risk management improvements
- Tax optimization strategies
- Performance targets
Integration Points
With Trading Analysis Agent
Trading CSV → Portfolio Analysis → Metrics + Edge
↓
(Feeds to projections)With Forecasting Agent
Metrics → Portfolio Analysis → Projections
↓
(Monte Carlo simulations)With Tax Planning
Projections → Portfolio Analysis → Tax Obligations
↓
(Quarterly payment schedule)Example Analysis
Input
- IB CSV: 10 trades over 28 days
- Initial capital: $2,000
- Current balance: $2,283.94
Output
Metrics:
- Win rate: 90% (9 wins, 1 loss)
- Average return: 3.58% per trade
- Trades/month: 18.5 (baseline)
- Total P&L: $283.94
Edge Identified:
- Intraday: 100% win rate, $1,020 profit
- Premarket (04:00-05:00): Best time window
- Recommendation: 100% intraday trading
Projections (3 years):
- Year 1: $5.2M
- Year 2: $50B
- Year 3: $3.2T
Risk:
- Max drawdown: -44% (GETY trade without stop)
- With 5% stops: -8.2% max
- Position sizing: 75% avg (should be 10%)
Tax (FL resident):
- Federal only: 37%
- Year 3 tax: $1.184T
- Quarterly reserves required
Recommendations:
- Implement 5% hard stops (critical)
- Reduce position sizing to 10% max
- 100% intraday trading (abandon swings)
- Set up tax reserve account (37% quarterly)
Performance Tracking
Track actual vs projected monthly:
| Month | Projected | Actual | Variance | Status |
| Jan | $2,500 | $2,284 | -8.6% | On track |
| Feb | $5,000 | — | — | Pending |
| Mar | $10,000 | — | — | Pending |
Known Limitations
- Simplified Projections: Uses compound factor without full Monte Carlo
- CSV Parsing: May need adjustment for different IB statement formats
- Edge Detection: Requires sufficient historical trades (10+ recommended)
- Tax Calculations: Simplified federal + state (consult CPA for exact)
- No Live Integration: CSV-based, not real-time
Future Enhancements
- Real-time performance dashboard
- Automatic CSV import (scheduled)
- Interactive charts and visualizations
- Multi-account aggregation
- Machine learning edge detection
- Automated tax form generation (1040-ES)
- Slack/email alerts for milestones
- Integration with brokerage APIs
Troubleshooting
Issue: CSV parsing fails
Solution: Verify IB statement format. Check for "Trades" section with proper columns.
Issue: No edge identified
Solution: Ensure sufficient trade history (10+ trades). Check time format in CSV.
Issue: Projections seem unrealistic
Solution: These are theoretical maximums. Use Monte Carlo for realistic ranges.
Issue: Tax calculations don't match
Solution: Consult CPA for exact calculations. This tool provides estimates only.
Support
For issues:
- Check CSV format (most common issue)
- Verify config YAML structure
- Review log output for errors
- Test with smaller datasets first
License: MIT (Part of astoreyai/claude-skills) Repository: https://github.com/astoreyai/claude-skills/
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