# Matlab Optimize Portfolio

Help users formulate and solve portfolio optimization problems using Financial...

- Repository: https://github.com/matlab/matlab-agentic-toolkit (1237 stars)
- Category: Engineering
- License: see repository
- Last updated: 2026-10-27
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-optimize-portfolio -g -a claude-code -y`
Codex: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-optimize-portfolio -g -a codex -y`
Cursor: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-optimize-portfolio -g -a cursor -y`
Gemini CLI: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-optimize-portfolio -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add matlab/matlab-agentic-toolkit`

## Description

Help users formulate and solve portfolio optimization problems using Financial Toolbox's Portfolio object. Covers mean-variance (Markowitz), maximum Sharpe ratio (tangency), and efficient frontier workflows. Use when users ask about portfolio optimization, Markowitz, efficient frontier, Sharpe ratio, or attempt to use generic solvers (quadprog, fmincon, ga, problem-based optimize) for portfolio problems.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Portfolio Optimization with Financial Toolbox

You are helping a user formulate and solve a portfolio optimization problem using MATLAB's Financial Toolbox `Portfolio` object.

## When to Use

- User wants to optimize a portfolio (minimize variance, maximize Sharpe ratio, trace efficient frontier)
- User asks about Markowitz, mean-variance, minimum-variance, or tangency portfolios
- User asks about the efficient frontier or target-return portfolios
- User is trying to use fmincon, quadprog, ga, or problem-based optimize for portfolio optimization (redirect to Portfolio object)
- User asks how to set up constraints for portfolio optimization (bounds, groups, turnover, one-way turnover, cardinality, semicontinuous)
- User asks about mean-variance with cardinality or semi-continuous constraints
- User gets errors from Portfolio, estimateMaxSharpeRatio, estimateFrontier, or related methods

## When NOT to Use

- User has a general optimization problem (QP, NLP, MILP) that is NOT financial asset allocation (e.g., filter design, resource allocation, mixture proportions), use `matlab-solve-optimization`
- User needs to retrieve market data from Bloomberg, FRED, or Haver Analytics, use `matlab-access-datafeed`
- User wants to predict returns or portfolio weights using neural networks or ML, use `matlab-train-network`
- User only wants to clean, explore, or summarize a returns table without optimization, use `matlab-analyze-data`
- User wants Experiment Manager parameter sweeps (not portfolio frontier), use `matlab-use-experiment-manager`
- User wants CVaR, MAD, or other non-mean-variance risk measures, use `PortfolioCVaR` or `PortfolioMAD` classes (not covered by this skill)

## Key Principle

**Always use the `Portfolio` class**, never let users manually code the optimization with `fmincon` or `quadprog`. The toolbox handles solver configuration, constraint management, and frontier computation automatically.

The rest: https://github.com/matlab/matlab-agentic-toolkit/blob/HEAD/skills-catalog/computational-finance/matlab-optimize-portfolio/SKILL.md