pfopt_mean_variance: 4 tools.
| Tool | What it does | Notes |
|---|---|---|
pfopt_mean_variance | Mean-variance optimal weights from a price history (or given expected returns and covariance): max Sharpe, min volatility, max quadratic utility, max return for a target volatility, or min volatility for a target return, with bounds, shorting, market neutrality, sector/group and linear constraints and L2, transaction-cost and tracking-error penalties. | |
pfopt_convex_objective | Minimises one convex objective from a fixed set under the same bounds, sector and linear constraints and penalty terms as pfopt_mean_variance: a log-barrier risk-budgeting portfolio, or the portfolio closest to a benchmark by ex-ante (weights and covariance) or ex-post (historical returns) tracking error. | |
pfopt_nonconvex_objective | Optimises an objective from a fixed set with a local gradient method, which admits nonconvex objectives and constraints (equal risk contribution, an exact volatility target, market neutrality with a Sharpe or return objective) but may stop at a local optimum. | |
pfopt_efficient_frontier | The mean-variance efficient frontier under the given bounds and constraints: annual volatility against expected return (and Sharpe) at each point with the weights of every frontier portfolio, the tangency (max Sharpe) and minimum-volatility portfolios, each asset’s own risk and return, and random portfolios. |
fincept_describe_tool.