Asset Allocation
Portfolio Optimisation
A quant library for portfolio construction and risk, spanning hierarchical and clustered allocation, coherent and spectral risk measures, copula tail modelling, and maximum-likelihood SDE fitting.
Builds allocations with Hierarchical Risk Parity, Nested Clustered Optimisation, and Hierarchical Equal Risk Contribution over Ledoit-Wolf-shrunk and Marchenko-Pastur-denoised covariance, with Black-Litterman view blending and Michaud resampling.
Adds convex programs in CVXPY for minimum CVaR, Entropic Value-at-Risk, and Conditional Drawdown-at-Risk, second-order stochastic dominance, and polynomial goal programming over mean, variance, skewness, and kurtosis.
Measures risk through entropic and spectral measures and Wang-transform distortion, models tails with generalised-Pareto and Hill extreme-value estimators and a Student t-copula fitted by maximum likelihood, and validates with Kupiec, Christoffersen, and Acerbi-Szekely backtests under a stationary bootstrap and deflated Sharpe ratios.