Statistical / ML for Quants
Factor models (CAPM, Fama-French), time series for volatility (ARIMA, GARCH), machine learning for signal generation, and rigorous backtesting — grounded entirely in real quant use cases.
4 modules~91 min total
Prerequisites
Probability and statistics (regression, hypothesis testing)Basic linear algebra (eigenvalues, OLS)Python (numpy, pandas, statsmodels)
Modules
01
Factor Models: CAPM, APT, and Fama-French
MediumStatistical / ML for QuantsFactor ModelsCAPMFama-FrenchRisk Premia
22 min
02
Time Series for Quants: ARIMA and GARCH
MediumStatistical / ML for QuantsTime SeriesARIMAGARCHVolatility Forecasting
22 min
03
ML in Signal Generation
HardStatistical / ML for QuantsMachine LearningAlpha SignalsRegularisationCross-Validation
25 min
04
Backtesting and Statistical Testing
HardStatistical / ML for QuantsBacktestingSharpe RatioMultiple Hypothesis TestingOverfitting
22 min