# Quant Analysis

> Quantitative finance analysis including portfolio optimization, risk modeling, and time series econometrics using jupyter_execute

- Skill: `zaoqu-liu/quant-analysis` (Agent Skill)
- Install (CLI): `npx skillmds@latest add zaoqu-liu/quant-analysis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/zaoqu-liu/quant-analysis/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: zaoqu-liu (https://skillmd.com/u/zaoqu-liu)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/zaoqu-liu/quant-analysis

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# Quantitative Analysis Skill

## Description
Perform quantitative finance research including data analysis, portfolio optimization, risk modeling, and econometric analysis.

## Tools Used
- `jupyter_execute` - Execute Python code for financial analysis (auto-switches to Jupyter)
- `jupyter_notebook` - Manage analysis notebooks
- `update_notebook` - Set up analysis cells in Jupyter
- `update_latex` - Write finance paper content to LaTeX editor
- `latex_compile` - Compile research papers (auto-switches to LaTeX editor)
- `update_notes` - Write analysis summaries and findings

## Capabilities

### Data Analysis
- Time series analysis of financial returns
- Cross-sectional regression (Fama-MacBeth, panel data)
- Event studies and abnormal return analysis
- Volatility modeling (GARCH family)

### Portfolio Optimization
- Mean-variance optimization (Markowitz)
- Black-Litterman model with views
- Risk parity and equal risk contribution
- Factor-based portfolio construction

### Risk Analysis
- Value-at-Risk (VaR) and Conditional VaR
- Stress testing and scenario analysis
- Copula-based dependency modeling
- Monte Carlo simulation

## Usage Patterns

### Analyze Returns
When user says: "Analyze the performance of [asset/portfolio]"
1. Load price data using pandas/yfinance
2. Calculate returns, volatility, Sharpe ratio
3. Plot cumulative returns and drawdowns
4. Run statistical tests (normality, autocorrelation)
5. Present findings with charts

### Build a Model
When user says: "Build a [pricing/risk/factor] model"
1. Clarify model specification and data requirements
2. Load and clean data
3. Estimate model parameters
4. Validate with out-of-sample testing
5. Report results with diagnostics