Quantitative Finance

A comprehensive guide for building robust backtesting frameworks for trading strategies. Covers common biases (look-ahead, survivorship, overfitting), implementation patterns including event-driven and vectorized backtesters, walk-forward optimization, Monte Carlo analysis, and performance metrics calculation.

A comprehensive reference guide for calculating portfolio risk metrics. Provides Python code patterns for Value at Risk (VaR), Conditional VaR, Sharpe ratio, Sortino ratio, maximum drawdown, and other risk measurements used in portfolio management and risk monitoring systems.

A comprehensive quantitative finance skill for building robust backtesting systems for trading strategies. It covers event-driven and vectorized backtesters, walk-forward optimization, Monte Carlo analysis, and risk metrics including VaR, CVaR, Sharpe ratio, and drawdown analysis.