quant-analyst

Perform quantitative analysis, financial modeling, and risk assessment for investment decisions.

1|1|Updated Aug 5, 2025

Search Tags:#quantitative analysis #financial modeling #risk management #portfolio optimization #backtesting #statistical analysis #algorithmic trading

Ready to run

npx skills add https://github.com/slantview/claude --skill quant-analyst-slantview

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: quant-analyst
Source: https://github.com/slantview/claude/tree/main/skills/quant-analyst
Command: npx skills add https://github.com/slantview/claude --skill quant-analyst-slantview

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, scipy, scikit-learn, statsmodels, yfinance, and includes scripts (resource) components.

What problem does it solve?

This Skill automates complex financial analysis, risk assessment, and quantitative modeling tasks, enabling data-driven investment and trading decisions.

Core Features & Use Cases

Financial Risk Analysis: Calculate Value at Risk (VaR), Expected Shortfall, and perform portfolio optimization.
Algorithmic Trading: Develop and backtest trading strategies using historical data.
Statistical Modeling: Perform time series analysis, correlation, and factor analysis on financial data.
Use Case: Analyze the risk and return profile of a potential stock portfolio, backtest a momentum trading strategy, and generate a comprehensive performance report.

Quick Start

Use the quant-analyst skill to fetch market data for AAPL and MSFT and calculate their portfolio metrics.

Frequently Asked Questions about quant-analyst

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

FAQPage Schema

How do I calculate Value at Risk and Expected Shortfall for a stock portfolio?▼

Portfolio optimization balances risk and return by applying statistical analysis to financial time series data. This Skill automates this process using numpy and pandas to calculate asset correlations and generate optimal weight allocations for your investment portfolio.

Can I backtest an algorithmic trading strategy using historical market data?▼

Yes, it supports time series analysis, correlation, and factor analysis on financial data. By leveraging statsmodels and scikit-learn, the Skill performs statistical modeling to identify trends and relationships within historical market data for quantitative analysis.

Do I need numpy and pandas installed for financial modeling tasks?▼

It leverages scikit-learn and statsmodels to perform statistical analysis on financial time series data. This approach enables you to model asset correlations, perform factor analysis, and backtest trading strategies using historical market data fetched via yfinance.

What is the best way to perform statistical analysis on financial time series data?▼

Risk management limits are handled by calculating VaR and Expected Shortfall to quantify potential portfolio losses. This Skill uses scipy and statsmodels to model statistical properties of financial time series, providing quantitative risk assessment for trading decisions.