covariance-forecasting

Here are 3 public repositories matching this topic...

AdarshArunEire / Eigenvector-Dynamics-Beyond-the-RMT-Null

RMT-calibrated financial eigenvector dynamics: separating genuine covariance rotation from sampling noise, testing forecastability on Grassmann and flag manifolds, and building geometry-aware covariance forecasts.

quantitative-finance manifold-learning spectral-analysis random-matrix-theory time-series-forecasting riemannian-geometry financial-machine-learning flag-manifold covariance-forecasting eigenvector-dynamics matrix-perturbation-theory

Updated Aug 5, 2026
Python

AdarshArunEire / Riemannian-Factor-Dynamics

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Riemannian Factor Dynamics: a SPD factor model built around a moving baseline in curved geometry

python r time-series quantitative-finance financial-econometrics covariance-estimation riemannian-geometry spd-manifold bures-wasserstein dynamic-factor-models covariance-forecasting

Updated Aug 31, 2026
Jupyter Notebook

chirindaopensource / how_trade_policy_uncertainty_alters_stock_tbill_relationships

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End-to-End Python implementation of Lacava's (2026) "Shifting Correlations" research. Features Numba-compiled GJR-GARCH volatility filtering, augmented DCC-X framework with exogenous Trade Policy Uncertainty integration, structural break testing, out-of-sample GMV optimization, and Model Confidence Set validation.

Updated Mar 29, 2026
Jupyter Notebook

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