risk-analysis

Quantify trading risk exposures across VaR, CVaR, drawdown, Monte Carlo, stress testing, and EVT tail metrics.

30.4k|4.9k|Updated Apr 1, 2026

Search Tags:#stress-testing #risk-analysis #monte-carlo #tail-risk #var #portfolio-monitoring #value-at-risk

Ready to run

npx skills add https://github.com/HKUDS/Vibe-Trading --skill risk-analysis-hkuds

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: risk-analysis
Source: https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/risk-analysis
Command: npx skills add https://github.com/HKUDS/Vibe-Trading --skill risk-analysis-hkuds

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill condenses the intricacies of portfolio risk measurement into a structured analysis that exposes VaR, CVaR, drawdowns, stress losses, and tail behavior so traders can spot vulnerabilities before they materialize.

Core Features & Use Cases

VaR & CVaR modeling contrasts historical, parametric, and Monte Carlo approaches to capture typical and extreme losses.
Stress testing walks through historical crises and hypothetical shocks to quantify scenario losses and stop-loss triggers.
Tail-risk diagnostics fit EVT models, kurtosis, skewness, and tail ratios so traders can judge whether exposures are fat-tailed.
Use Case: Run the skill after a backtest to report volatility, drawdown, stress scenarios, and EVT tail type before adjusting allocations.

Quick Start

Use the risk-analysis skill to report VaR, CVaR, drawdown, and simulated stress losses for your latest return series.

Frequently Asked Questions about risk-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I calculate Value at Risk and CVaR for a portfolio?▼

Portfolio VaR and CVaR are calculated by processing return series and portfolio weights to contrast historical, parametric, and Monte Carlo approaches. This captures both typical and extreme losses across your portfolio exposure.

How do I run stress tests on historical crises and hypothetical market shocks?▼

Portfolio stress testing walks through historical crises and hypothetical shocks to quantify scenario losses and identify stop-loss triggers. You provide return or equity series and optional benchmarks to output descriptive statistics.

What is the best way to measure tail risk and check for fat-tailed distributions?▼

Tail-risk diagnostics fit EVT models, kurtosis, skewness, and tail ratios to determine whether exposures are fat-tailed. This reveals extreme loss vulnerabilities hidden in standard volatility metrics.

Can I use Monte Carlo simulation to compare against historical portfolio losses?▼

Monte Carlo simulation contrasts with historical and parametric approaches to capture typical and extreme portfolio losses. You process return series and portfolio weights to output simulated scenario losses.

How do I report drawdowns and volatility after running a backtest?▼

Run risk analysis after a backtest to report volatility, drawdown, stress scenarios, and EVT tail type before adjusting allocations. The skill processes return series and portfolio weights to output these descriptive statistics.

When do I need Extreme Value Theory for portfolio risk monitoring?▼

Extreme Value Theory is needed when evaluating tail-risk diagnostics to judge whether portfolio exposures are fat-tailed. EVT tail metrics reveal extreme loss behavior that standard risk metrics may miss.