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Portfolio Risk

skill-qunyou-agent-finance-skills-portfolio-risk · by qunyou-agent

Analyzes portfolio risk and performance metrics. Computes Value at Risk (VaR), Sharpe ratio, Sortino ratio, beta, correlation matrices, drawdown analysis, and position sizing recommendations. Trigger when the user requests risk analysis, portfolio optimization, or performance attribution.

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Install

$ agentstack add skill-qunyou-agent-finance-skills-portfolio-risk

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Portfolio Risk

Analyzes portfolio risk and recommends position sizing and diversification.

Real Code Reference

  • tradinglearn/backtest/backtester.py — Backtester._calculate_performance() computes Sharpe, max drawdown, win rate, total return, CAGR
  • tradinglearn/utils/parameter_optimizer.py — plot_optimization_results() heatmaps: return, Sharpe, drawdown, win rate
  • tradinglearn/pytdx2/backtest.py — BacktestEngine tracks per-trade P&L for risk analysis

Risk Metrics

  • VaR: historical simulation, parametric, Monte Carlo
  • CVaR (Expected Shortfall): average loss beyond VaR
  • Maximum Drawdown: peak-to-trough with recovery duration
  • Volatility: annualized std of returns

Performance Metrics

  • Sharpe Ratio: (R - Rf) / sigma
  • Sortino Ratio: downside-only volatility
  • Calmar Ratio: annual return / max drawdown
  • Information Ratio: active return / tracking error

Portfolio Analysis

  • Correlation matrix between holdings
  • Beta to market benchmark
  • Position concentration (Herfindahl index)
  • Risk parity weights

Usage

from backtest.backtester import Backtester

bt = Backtester(initial_capital=100000.0)
bt.run_backtest(data, MyStrategy, params)
perf = bt.get_performance()
# {'total_return': 0.15, 'annual_return': 0.12, 'sharpe_ratio': 1.2,
#  'max_drawdown': -0.08, 'win_rate': 0.55, 'total_trades': 42}
portfolio = bt.get_portfolio()
# DataFrame with: portfolio_value, position, cash, returns

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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