Portfolio Optimizer

PHASE 1

Mean-variance, max-Sharpe, risk parity and the efficient frontier with constraints.

Planned capabilities

›Expected returns from historical mean, exponential weighting or manual entry.
›Covariance from the sample matrix, EWMA with adjustable lambda, or shrinkage toward the diagonal.
›Minimum variance, maximum Sharpe, risk parity, equal weight and inverse volatility.
›Efficient frontier sweep with the capital market line, tangency portfolio and clickable points.
›Constraints: long-only, per-asset bounds, position count, target return or volatility.
›Weight stability through bootstrap resampling, plus turnover against a pasted current portfolio.

Data readiness

datasets available in the workspace.

Status

This module is scaffolded and wired into the workspace. It will be built out in phase 1, using the shared math library and the datasets you generate or upload.