risk-calculator

Name: risk-calculator
Availability: InStock
Author: kayzaa

Calculate portfolio risk metrics including VaR, Sharpe ratio, and position sizing.

5|1|Updated Feb 9, 2026

Search Tags:#analysis #portfolio #trading #risk #position sizing #var #sharpe ratio

Ready to run

npx skills add https://github.com/kayzaa/k.i.t.-bot --skill risk-calculator

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: risk-calculator
Source: https://github.com/kayzaa/k.i.t.-bot/tree/main/skills/risk-calculator
Command: npx skills add https://github.com/kayzaa/k.i.t.-bot --skill risk-calculator

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides in-depth analysis of your trading portfolio's risk, helping you understand potential losses, optimize position sizes, and make more informed trading decisions.

Core Features & Use Cases

Risk Metrics: Calculate Value at Risk (VaR), Conditional VaR (CVaR), Sharpe Ratio, Sortino Ratio, and Maximum Drawdown.
Position Sizing: Determine optimal trade sizes using methods like Kelly Criterion and fixed risk percentage.
Correlation Analysis: Understand how assets in your portfolio move together to improve diversification.
Use Case: Before entering a new trade, use the risk calculator to determine the appropriate position size based on your risk tolerance and the asset's volatility, ensuring you don't over-expose your portfolio.

Quick Start

Run a full portfolio risk analysis using the risk calculator.

Frequently Asked Questions about risk-calculator

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

FAQPage Schema

How do I calculate Value at Risk and Sharpe ratio for a trading portfolio?▼

Portfolio risk analysis calculates metrics like Value at Risk and Sharpe ratio by running statistical computations on your asset data. It evaluates potential losses and risk-adjusted returns to support quantitative trading strategies.

What is the best way to determine optimal position sizing before entering a trade?▼

Determining optimal position sizing involves calculating appropriate trade sizes based on your risk tolerance and asset volatility. Methods like the Kelly Criterion and fixed risk percentage help prevent over-exposure by aligning trade sizes with your portfolio's risk parameters.

How does correlation analysis improve portfolio diversification?▼

Correlation analysis improves diversification by measuring how assets in your portfolio move together. Understanding these statistical relationships helps you construct a portfolio with lower correlated assets, reducing overall risk exposure during market fluctuations.

Do I need numpy and pandas to run quantitative risk analysis?▼

Yes, quantitative risk analysis requires numpy, pandas, and scipy for statistical computations and data manipulation. These libraries provide the foundational mathematical operations needed to calculate financial risk metrics and process portfolio data.

Can I calculate Conditional VaR and Maximum Drawdown for my trading strategies?▼

Yes, you can calculate Conditional VaR and Maximum Drawdown alongside standard risk metrics. These advanced calculations assess the expected loss beyond the VaR threshold and the largest peak-to-trough decline, providing deeper insight into portfolio risk.

What are the limitations of using statistical models for portfolio risk management?▼

Statistical risk management models rely on historical data and probability assumptions, meaning they cannot predict unprecedented market events. Metrics like VaR and Sharpe ratio should guide trading decisions rather than guarantee future performance.