quant-analyst

Installation
Summary

Expert quantitative finance, algorithmic trading, and financial data analysis using Python scientific computing.

  • Covers algorithmic trading strategy development, backtesting frameworks, and signal generation with walk-forward validation to prevent overfitting
  • Implements risk models including VaR, CVaR, Greeks calculations, and Monte Carlo simulations for derivatives pricing
  • Provides portfolio optimization techniques (mean-variance, Black-Litterman, risk parity) with transaction cost and rebalancing considerations
  • Specializes in time series analysis, factor modeling, and market microstructure using vectorized NumPy/Pandas operations on financial data
SKILL.md

Quantitative Analyst

Purpose

Provides expertise in quantitative finance, algorithmic trading strategies, and financial data analysis. Specializes in statistical modeling, risk analytics, and building data-driven trading systems using Python scientific computing stack.

When to Use

  • Building algorithmic trading strategies or backtesting frameworks
  • Performing statistical analysis on financial time series data
  • Implementing risk models (VaR, CVaR, Greeks calculations)
  • Creating portfolio optimization algorithms
  • Developing quantitative pricing models for derivatives
  • Analyzing market microstructure and order book dynamics
  • Building factor models for asset returns
  • Implementing Monte Carlo simulations for financial instruments

Quick Start

Invoke this skill when:

  • Building algorithmic trading strategies or backtesting frameworks
  • Performing statistical analysis on financial time series data
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GitHub Stars
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First Seen
Jan 24, 2026