Risk Metrics Calculation
SkillMonitoring & opsrisk-metrics-calculation is a skill that lets an AI agent calculate portfolio risk metrics, including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. It is useful when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.
Use Risk Metrics Calculation in Claude, ChatGPT or Ahel Desktop
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Then ask your AI: use the Risk Metrics Calculation skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
No other account needed.
Have an AI agent setup that can load skills.
What your AI can do with it
- Calculate Value at Risk (VaR) for a portfolio
- Calculate Conditional Value at Risk (CVaR)
- Compute Sharpe ratio and Sortino ratio
- Perform drawdown analysis on a portfolio
- Support implementing risk limits
- Support building risk monitoring systems
Getting started
- Have an AI agent setup that can load skills.
- Add the risk-metrics-calculation skill to the agent's available skills.
- Provide the portfolio data needed for the metrics you want.
- Ask the agent to calculate the desired risk metrics, such as VaR or Sharpe ratio.
What this skill tells your AI
The instructions your AI receives, as published by wshobson/agents in plugins/quantitative-trading/skills/risk-metrics-calculation/SKILL.md and read by ahel’s review.
Comprehensive risk measurement toolkit for portfolio management, including Value at Risk, Expected Shortfall, and drawdown analysis.
When to Use This Skill
- Measuring portfolio risk
- Implementing risk limits
- Building risk dashboards
- Calculating risk-adjusted returns
- Setting position sizes
- Regulatory reporting
Core Concepts
1. Risk Metric Categories
| Category | Metrics | Use Case |
|---|---|---|
| Volatility | Std Dev, Beta | General risk |
| Tail Risk | VaR, CVaR | Extreme losses |
| Drawdown | Max DD, Calmar | Capital preservation |
| Risk-Adjusted | Sharpe, Sortino | Performance |
2. Time Horizons
Intraday: Minute/hourly VaR for day traders
Daily: Standard risk reporting
Weekly: Rebalancing decisions
Monthly: Performance attribution
Annual: Strategic allocation
Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
Best Practices
Do's
- Use multiple metrics - No single metric captures all risk
- Consider tail risk - VaR isn't enough, use CVaR
- Rolling analysis - Risk changes over time
- Stress test - Historical and hypothetical
- Document assumptions - Distribution, lookback, etc.
Don'ts
- Don't rely on VaR alone - Underestimates tail risk
- Don't assume normality - Returns are fat-tailed
- Don't ignore correlation - Increases in stress
- Don't use short lookbacks - Miss regime changes
- Don't forget transaction costs - Affects realized risk
Signals
- GitHub stars
- 40k
- Forks
- 4k
- Last commit
- Sep 2026
Questions
- What metrics can it calculate?
- It calculates VaR, CVaR, Sharpe ratio, Sortino ratio, and drawdown analysis.
- When should it be used?
- Use it when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.
Advanced
- Item type
- skill
- Key
risk-metrics-calculation-wshobson- Source
- github.com/wshobson/agents
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