Distributional crypto-return forecasting via Wasserstein-geodesic extrapolation in quantile-function space. WGeo family wins 12/12 (asset × horizon) cells over 6.75y walk-forward CRPS vs GARCH and classical baselines. v0.4.

MSc thesis investigating whether rough volatility models improve out-of-sample volatility forecasting performance relative to HAR-RV

HAR-RV volatility forecasting baseline with ML overlay — USDZAR/JSE Top 40

A comprehensive volatility forecasting project using ARIMA-GARCH family models, statistical diagnostics, realized volatility analysis, OHLC-based realized volatility estimators and backtesting on financial time series data.