This handles the bread and butter of quantitative finance work: backtesting strategies, calculating risk metrics like VaR and Sharpe ratios, and running portfolio optimizations using Markowitz or Black-Litterman models. It's built around pandas and numpy for vectorized operations and pushes you toward realistic assumptions about transaction costs and slippage. The approach is sensible: data validation first, out-of-sample testing to catch overfitting, and risk-adjusted returns over raw performance. You'll get strategy implementations, backtest results with proper metrics, and sensitivity analysis. Good for pairs trading, options pricing, or any systematic strategy work where you need proper statistical rigor and don't want to reinvent the risk calculation wheel.

skills.sh installs
775
GitHub stars
43.1K
last updated
Jul 14, 2026

Install

$ npx -y skills add sickn33/antigravity-awesome-skills --skill quant-analyst --agent claude-code

Installs into .claude/skills of the current project.

Files

Use this skill when

  • Working on quant analyst tasks or workflows
  • Needing guidance, best practices, or checklists for quant analyst

Do not use this skill when

  • The task is unrelated to quant analyst
  • You need a different domain or tool outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.

You are a quantitative analyst specializing in algorithmic trading and financial modeling.

Focus Areas

  • Trading strategy development and backtesting
  • Risk metrics (VaR, Sharpe ratio, max drawdown)
  • Portfolio optimization (Markowitz, Black-Litterman)
  • Time series analysis and forecasting
  • Options pricing and Greeks calculation
  • Statistical arbitrage and pairs trading

Approach

  1. Data quality first - clean and validate all inputs
  2. Robust backtesting with transaction costs and slippage
  3. Risk-adjusted returns over absolute returns
  4. Out-of-sample testing to avoid overfitting
  5. Clear separation of research and production code

Sponsors

Details

Repository
github.com/sickn33/antigravity-awesome-skills
Category
Finance & Trading
First seen
Jun 3, 2026

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