risk-analysis

Compute portfolio VaR/CVaR, maximum drawdown, and tail risk via historical, parametric, Monte Carlo, and scenario stress tests.

Updated Apr 14, 2026
One-click install
npx skills add https://github.com/loanntc/Paave --skill risk-analysis-loanntc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: risk-analysis
Source: https://github.com/loanntc/Paave/tree/main/skills/risk-analysis
Command: npx skills add https://github.com/loanntc/Paave --skill risk-analysis-loanntc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps you measure and explain portfolio downside risk by turning historical returns and scenario assumptions into actionable risk metrics for decision-making.

Core Features & Use Cases

  • VaR/CVaR (ES) risk measurement: compute Value at Risk and Conditional VaR using historical simulation, parametric (normal), and Monte Carlo methods.
  • Maximum drawdown analysis: derive worst peak-to-trough loss, recovery timing, and drawdown duration from an equity or net-value series.
  • Stress testing & tail-risk (EVT) analysis: run historical and hypothetical scenario shock analysis and fit extreme tails using a POT (GPD) approach.

Use case: evaluate whether a backtest or allocation plan breaches risk-control constraints by comparing VaR/CVaR, drawdown severity, Monte Carlo loss probabilities, and scenario-driven portfolio losses.

Quick Start

Use the risk-analysis skill to compute VaR and CVaR at 95% and 99% for your return series, run Monte Carlo with 10,000 paths, and produce a stress-test report that includes maximum drawdown and EVT tail fitting.

Frequently Asked Questions about risk-analysis

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

FAQPage Schema
How do I calculate VaR and CVaR for a portfolio return series?▼

You can calculate VaR and CVaR using historical simulation, parametric normal, or Monte Carlo methods. The skill computes quantile-based loss estimations across your return series to produce coherent risk metrics.

What is the best way to run Monte Carlo stress testing on portfolio allocations?▼

Monte Carlo stress testing simulates 10,000 portfolio paths to project loss probabilities and evaluate whether your allocation plan breaches defined risk-control constraints under various market scenarios.

How does extreme value theory apply to tail-risk analysis in finance?▼

Extreme value theory applies to tail-risk analysis by fitting a Peaks-Over-Threshold (POT) model with a Generalized Pareto Distribution to estimate the probability of severe, out-of-sample portfolio losses.

Can I measure maximum drawdown and recovery timing from an equity time series?▼

Yes, maximum drawdown analysis derives worst peak-to-trough losses, recovery timing, and drawdown duration directly from your equity or net-value time series to evaluate historical portfolio performance.

Does scenario shock stress testing work with custom portfolio weights and positions?▼

Scenario shock stress testing applies hypothetical market shocks directly to your portfolio positions and weights, computing resulting portfolio losses for backtest evaluation and allocation risk controls.