R package for adaptive correlation and covariance matrix shrinkage.
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Updated
Jan 23, 2019 - R
R package for adaptive correlation and covariance matrix shrinkage.
Reproducibility repository for 'Beyond De Prado and Cotton: Hierarchical and Iterative Methods for General Mean-Variance Portfolios' (Wuebben): Python code and result artifacts for HRP-μ, HRP-Σμ, and the CRISP iterative shrinkage solver.
Adaptive Monitoring and Real-World Evaluation of Agentic AI Systems
Paper VII of Statistical Pharmacology via Kakutani Dichotomy: kakutani_pharma, a Python pipeline for Kakutani indices of MD conformational ensembles. Ledoit-Wolf regularized CKI with an exact three-way decomposition, split-trajectory null subtraction, within-half block bootstrap, and pocket-centred shell-scaling exponents. Validated on a synthetic
Portfolio input-estimation bridge that applies mean/covariance shrinkage and exports Black-Litterman-ready inputs.
Robust portfolio optimization in Python using rolling out-of-sample validation, covariance shrinkage, concentration constraints, risk parity, turnover and transaction costs.
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