| name | portfolio-analytics |
| description | Portfolio management, optimization, backtesting, and performance analytics |
| always | false |
Portfolio Analytics
This skill enables Finclaw to manage and analyze an investment portfolio.
Tools Available
portfolio — Full portfolio management: positions, P&L, optimization, backtesting, tearsheets
Portfolio Workflow
Getting Started
When a user wants to track a portfolio:
- Use
portfolio(action='add_position', symbol='AAPL', shares=100, cost_basis=150.00, date='2025-01-15')
- After adding all positions, run
portfolio(action='summary') to show the current state
- Suggest running
portfolio(action='analyze') for risk/return metrics
Regular Review
During weekly reviews:
portfolio(action='summary') — Current P&L and allocation
portfolio(action='analyze', period='1y') — Key metrics
- Cross-reference with
macro_monitor(action='regime_check') for risk context
- Flag concentration risk if any position is >20% of portfolio
- Suggest rebalancing if actual weights deviate >5% from targets
Optimization
When asked to optimize:
- Default to
efficient_frontier for most users
- Use
hrp (Hierarchical Risk Parity) for diversification-focused portfolios
- Use
black_litterman when the user has strong market views
- Always show both current and recommended weights
- Explain the trade-offs: "Optimizing for max Sharpe suggests reducing AAPL from 25% to 18% and increasing XLF from 5% to 12%"
Performance Reporting
portfolio(action='tearsheet') generates comprehensive performance metrics
- Always include: Sharpe, Sortino, max drawdown, CAGR
- Compare to SPY as benchmark
- Use in weekly reports via
report(action='weekly')
Communication Style
- Lead with the bottom line: "Portfolio is up 3.2% this week, outperforming SPY by 1.1%"
- Flag risks proactively: "Concentration warning: 45% of portfolio is in Technology"
- Suggest actionable improvements: "Adding 10% TLT would reduce portfolio volatility by ~15%"