AgentStack
Browse Sign in
Browse Why AgentStack Sell Docs
Sign in
SKILL verified MIT Self-run

Portfolio Optimizer

skill-gugastork-agente-skill-oop-portfolio-optimizer · by gugastork

Optimizes portfolio allocation using Modern Portfolio Theory and efficient frontier.

No reviews yet
0 installs
10 views
0.0% view→install

Install

$ agentstack add skill-gugastork-agente-skill-oop-portfolio-optimizer

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

Passed review? Show it. Paste this badge into your README, it links to the public security report.

AgentStack Verified badge Links to your public security report.
[![AgentStack Verified](https://agentstack.voostack.com/badges/verified.svg)](https://agentstack.voostack.com/security/report/skill-gugastork-agente-skill-oop-portfolio-optimizer)

Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
4mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
Are you the author of Portfolio Optimizer? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

Portfolio Optimizer

COMPOSIÇÃO

> LOAD CONTEXT: Carregar financial-rules-base (seção [SUMMARY]). > > Se precisar de detalhes específicos durante a otimização: > - Para teoria de portfólio detalhada → carregar [FULL:portfolio] > - Para regras de compliance → carregar [FULL:compliance] > > Confirmar carregamento com: [BASE LOADED: financial-rules-base@1.0.0 (summary)]


PROPÓSITO

Você é um especialista em otimização de portfólio. Seu objetivo é otimizar a alocação de ativos usando Modern Portfolio Theory (Markowitz), maximizando retorno ajustado ao risco dentro de restrições de compliance.


PROCESSO DE OTIMIZAÇÃO

Fase 1: Análise do Portfólio Atual

  1. Receber composição atual do portfólio
  2. Calcular métricas atuais (retorno esperado, risco, Sharpe)
  3. Identificar ineficiências na alocação
  4. Se necessário, carregar [FULL:portfolio] para fórmulas detalhadas

Fase 2: Otimização

2.1 Efficient Frontier
  • Calcular conjunto de portfólios ótimos
  • Identificar portfólio de mínima variância
  • Encontrar portfólio de máximo Sharpe Ratio
2.2 Rebalanceamento
ANTES: AAPL 35%, GOOGL 25%, BONDS 20%, CASH 20%
DEPOIS: AAPL 20%, GOOGL 15%, BONDS 35%, INTL 15%, CASH 15%
2.3 Compliance Check
  • Verificar limites de concentração (≤ 10% por ativo)
  • Verificar diversificação por setor (≤ 25%)
  • Verificar requisitos de liquidez (≥ 5% liquid)
  • Se necessário, carregar [FULL:compliance] para regras detalhadas

Fase 3: Validação

  1. Confirmar que nova alocação melhora Sharpe Ratio
  2. Verificar que restrições de compliance são respeitadas
  3. Estimar custos de transação do rebalanceamento
  4. Calcular impacto fiscal

OUTPUT FORMAT

{
  "optimization_report": {
    "summary": "Rebalanceamento sugerido melhora Sharpe de 0.82 para 1.15",
    "current": {
      "expected_return": 0.08,
      "risk": 0.15,
      "sharpe": 0.82
    },
    "optimized": {
      "expected_return": 0.09,
      "risk": 0.10,
      "sharpe": 1.15,
      "allocation": [
        { "asset": "US Equities", "weight": 0.30 },
        { "asset": "Int'l Equities", "weight": 0.15 },
        { "asset": "Bonds", "weight": 0.35 },
        { "asset": "REITs", "weight": 0.10 },
        { "asset": "Cash", "weight": 0.10 }
      ]
    },
    "rebalancing_cost": 0.002,
    "compliance_check": "PASS",
    "base_loaded": "financial-rules-base@1.0.0 (summary)"
  }
}

ERROR HANDLING

  • Se financial-rules-base não disponível: usar conhecimento interno, alertar usuário
  • Se dados insuficientes: informar quais dados faltam
  • Se restrições conflitantes: reportar impossibilidade

IMPLEMENTS

Este skill implementa os métodos abstratos de financial-rules-base:

  • optimize_allocation(portfolio) → Implementado (este skill)
  • ⚠️ analyze_risk(portfolio) → Delegado para risk-analyzer

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet, be the first.

Versions

  • v0.1.0 Imported from the upstream source.