Introduction

Why Quantitative Statistics?

Every quantitative finance strategy rests on statistical foundations. Before you can backtest a trading strategy, optimize a portfolio, or price a derivative, you need tools to measure returns, quantify risk, and test hypotheses. This course builds those tools from scratch in pure Python.

You will implement:

  • Return Analysis — Log vs arithmetic returns, moments, rolling statistics, covariance and correlation
  • Risk Metrics — Normal distribution, historical volatility, drawdown, Sharpe and Sortino ratios
  • Statistical Testing — Beta and alpha, t-tests, OLS regression, R-squared, Jarque-Bera
  • Simulation — Monte Carlo sampling via Box-Muller, bootstrap confidence intervals
Next →