portfolio
Construcción y optimización cuantitativa de portafolios: Markowitz (scipy.optimize + Monte Carlo), Black-Litterman (prior CAPM, views absolutas/relativas, posterior bayesiano), HRP/HERC/NCO (clustering jerárquico, risk parity, NCO con restricciones). Todo flat numpy + scipy, sin Riskfolio-Lib ni PyPortfolioOpt.
Profile →npx skills add gauss314/skills --skill portfolio --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Portfolio — Optimización Cuantitativa de Portafolios Este skill implementa **3 enfoques de optimización de portafolios** desde el material del curso (notebook `Clase_08_teoria_2025_portafolio.ipynb` y PDF `Portafolios 2025 Ucema.pdf`): 1. **Markowitz / Media-Varianza** — Optimización convexa vía `scipy.optimize` + simulación Monte Carlo + frontera eficiente + CML. 2. **Black-Litterman** — Combin
What does the portfolio skill do?
Construcción y optimización cuantitativa de portafolios: Markowitz (scipy.optimize + Monte Carlo), Black-Litterman (prior CAPM, views absolutas/relativas, posterior bayesiano), HRP/HERC/NCO (clustering jerárquico, risk parity, NCO con restricciones). Todo flat numpy + scipy, sin Riskfolio-Lib ni PyPortfolioOpt.
How do I install it?
Run `npx skills add gauss314/skills --skill portfolio --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From gauss314/skills, a repository with 172 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.