Zaoqu-Liu/quant-analysis
skills/prismer-quant-analysis/SKILL.md
Quantitative finance analysis including portfolio optimization, risk modeling, and time series econometrics using jupyter_execute
$ install --global
skillsauthnpx skillsauth add Zaoqu-Liu/ScienceClaw quant-analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- quant-analysis
- description:
- Quantitative finance analysis including portfolio optimization, risk modeling, and time series econometrics using jupyter_execute
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 notebooksupdate_notebook- Set up analysis cells in Jupyterupdate_latex- Write finance paper content to LaTeX editorlatex_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]"
- Load price data using pandas/yfinance
- Calculate returns, volatility, Sharpe ratio
- Plot cumulative returns and drawdowns
- Run statistical tests (normality, autocorrelation)
- Present findings with charts
Build a Model
When user says: "Build a [pricing/risk/factor] model"
- Clarify model specification and data requirements
- Load and clean data
- Estimate model parameters
- Validate with out-of-sample testing
- Report results with diagnostics
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