Quantitative Finance

This skill provides comprehensive documentation for building production-grade backtesting systems for trading strategies. It covers common pitfalls like look-ahead bias and survivorship bias, includes implementation patterns for event-driven and vectorized backtesters, walk-forward optimization, Monte Carlo analysis, and performance metrics calculation.

This skill provides comprehensive documentation and Python code examples for calculating portfolio risk metrics. It covers Value at Risk (VaR), Conditional VaR (CVaR/Expected Shortfall), Sharpe and Sortino ratios, drawdown analysis, and stress testing methodologies for quantitative finance applications.