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.
pythonjupyter-notebookeconometricsportfolio-optimizationquantitative-financenumbaasset-pricingrisk-managementtime-series-analysisfinancial-econometricsmodel-confidence-setvolatility-modelinggarch-modelsmultivariate-garchdynamic-conditional-correlationstructural-breakstrade-policy-uncertaintycorrelation-modelingcovariance-forecastingsafe-haven-assets
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Updated
Mar 29, 2026 - Jupyter Notebook