alloc_optimize | Optimal portfolio weights for one of 26 risk measures (variance, MAD, CVaR, EVaR, tail Gini, drawdowns, …) and an objective (minimum risk, maximum utility, maximum return/risk ratio, maximum return), on historical estimates or a Black-Litterman, factor-model, Black-Litterman-on-factors or entropy-pooling model, under any mix of constraints. | |
alloc_efficient_frontier | The efficient frontier of a risk measure under the same models and constraints as alloc_optimize: points portfolios from minimum risk to maximum return. | |
alloc_owa | Portfolio optimising an ordered-weighted-average risk measure (a weighted sum of the sorted portfolio returns) such as the Gini mean difference, weighted CVaR, tail Gini, ranges or L-moments. | |
alloc_worst_case | Worst-case (robust) mean-variance portfolio: optimises the objective against the least favourable mean and covariance inside box or elliptical uncertainty sets estimated by bootstrap, normal simulation or a delta band. | |
alloc_mvsk | Portfolio optimising the first four moments together (mean, variance, skewness, kurtosis) through a semidefinite relaxation of coskewness and cokurtosis, at most 20 assets. | |
alloc_build_constraints | Builds the matrices an optimizer receives from rule rows and shows them: weight rules as A w <= B, risk contribution rules, factor-exposure rules, integer (cardinality, exclusive, joint) rules, hierarchical-portfolio bounds, risk budget vectors, Black-Litterman P/Q and entropy-pooling P/Q. | |
