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risk-analysis

Calculate VaR, CVaR, and maximum drawdown for financial assets.

2|Updated May 13, 2026
Search Tags:#stress testing#VaR#CVaR#Monte Carlo simulation#risk measurement
One-click install
npx skills add https://github.com/thanhtai040805/AI_Invest --skill risk-analysis-thanhtai040805
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: risk-analysis
Source: https://github.com/thanhtai040805/AI_Invest/tree/main/ai-engine/app/domain/services/quant/skills_data/risk-analysis
Command: npx skills add https://github.com/thanhtai040805/AI_Invest --skill risk-analysis-thanhtai040805

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scipy, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive framework for measuring and analyzing financial risk, including VaR/CVaR, max drawdown, Monte Carlo simulation, and historical scenario stress testing.

Core Features & Use Cases

  • Risk Measurement: Calculates Value at Risk (VaR), Conditional Value at Risk (CVaR), and maximum drawdown for financial assets.
  • Monte Carlo Simulation: Simulates potential future prices of financial instruments based on historical data and statistical models.
  • Stress Testing: Evaluates the impact of extreme market scenarios on a portfolio's performance.
  • Use Case: Utilize this Skill to assess the risk profile of a portfolio before making investment decisions.

Quick Start

Run the risk-analysis skill to calculate the 95% VaR for a given portfolio over a 1-day horizon.

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 financial portfolio?▼

To calculate VaR and CVaR for a financial portfolio, this Skill computes Value at Risk, Conditional Value at Risk, and maximum drawdown using historical asset data processed through pandas and numpy for statistical measurement.

How does Monte Carlo simulation work for financial risk measurement?▼

Monte Carlo simulation for risk measurement works by simulating potential future prices of financial instruments based on historical data and statistical models to evaluate potential portfolio performance under varied market conditions.

Can I perform stress testing on a portfolio using historical scenarios with pandas and numpy?▼

Yes, you can perform stress testing on a portfolio using historical scenarios with pandas and numpy, as this Skill evaluates the impact of extreme market scenarios on financial asset performance.

What is the best way to assess maximum drawdown for financial assets?▼

The best way to assess maximum drawdown for financial assets is using quantitative risk measurement frameworks that calculate peak-to-trough declines alongside VaR and CVaR to evaluate the complete risk profile.

Do I need scipy and matplotlib to run Monte Carlo simulations for risk analysis?▼

Yes, you need scipy and matplotlib to run Monte Carlo simulations for risk analysis, as these dependencies provide the necessary statistical distribution functions and visualization outputs for financial data.

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