Tearsheet

This project develops a Python application that generates a quantitative performance tear sheet from daily strategy and benchmark return data. It validates input data, calculates performance, risk and benchmark comparison metrics, including annualised return, volatility, Sharpe ratio, Sortino ratio, drawdown, alpha, beta, Value at Risk and expected shortfall, then produces a CSV summary and a six-panel chart showing portfolio growth, drawdowns, rolling metrics, return distribution and monthly performance.