risk-metrics-calculation
Calculate portfolio risk metrics
You need accurate risk measurements for portfolio management. This skill provides formulas and examples for VaR, Sharpe ratio, drawdowns, and other key metrics.
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Using "risk-metrics-calculation". Calculate risk metrics for my strategy returns
Expected outcome:
- Annual volatility: 15.2%
- Sharpe ratio: 0.85
- Max drawdown: -12.4%
- 95% VaR: -2.1% daily
- Current drawdown: -3.8%
Using "risk-metrics-calculation". Show portfolio risk decomposition
Expected outcome:
- Total portfolio volatility: 12.3%
- Asset A contribution: 4.2%
- Asset B contribution: 5.1%
- Asset C contribution: 3.0%
- Diversification ratio: 1.32
Security Audit
SafeDocumentation-only skill containing Python code examples for financial risk metrics. No executable code, file access, or network calls. Pure educational content matching stated purpose. Pre-computed static findings (100/100 risk) are false positives from scanner misidentifying Python f-strings as shell commands and financial abbreviations as cryptographic algorithms.
Risk Factors
🌐 Network access (4)
Quality Score
What You Can Build
Risk model implementation
Reference implementation for VaR, CVaR, and drawdown calculations in Python.
Risk reporting templates
Standardized formulas for weekly risk reports and limit monitoring.
Risk calculation library
Code snippets for building risk management systems and dashboards.
Try These Prompts
Calculate volatility, Sharpe ratio, and max drawdown for this return series using the formulas provided.
Compute 95% historical VaR and CVaR for these daily returns and explain what the numbers mean.
Using the portfolio risk class, calculate total portfolio volatility and component risk contributions.
Implement 63-day rolling volatility and Sharpe ratio for monitoring risk changes over time.
Best Practices
- Use multiple risk metrics for comprehensive analysis
- Consider tail risk with both VaR and CVaR
- Apply appropriate time horizons for your strategy
Avoid
- Relying solely on volatility as risk measure
- Ignoring drawdown periods in analysis
- Using inappropriate confidence levels