SKILL verified MIT Self-run

Portfolio Construction

Name: Portfolio Construction
Availability: InStock
Author: nutdnuy

skill-nutdnuy-self-driving-portfolio-skill-portfolio-construction · by nutdnuy

This skill should be used when the user asks to "compare portfolio construction methods", "run risk parity", "build a minimum-variance portfolio", or generate IPS-constrained SAA candidates.

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$ agentstack add skill-nutdnuy-self-driving-portfolio-skill-portfolio-construction

✓ 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.

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Reliability & compatibility

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● 26d ago

Declared compatibility

Claude CodeClaude Desktop

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

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About

portfolio-construction

Ten portfolio-construction methods, each producing one proposal that respects IPS hard constraints (long-only, sum-to-one, per-ticker box).

Methods

| ID | Description | | --------------------- | -------------------------------------------------------- | | equal_weight | 1/N | | inverse_vol | weights ∝ 1/σ | | min_variance | argmin wᵀΣw | | max_sharpe | argmax (wᵀμ − r_f) / √(wᵀΣw) | | risk_parity | equal risk contribution | | hrp | Hierarchical Risk Parity (Lopez de Prado) | | max_diversification | argmax (wᵀσ) / √(wᵀΣw) | | black_litterman | BL with regime-implied views | | mvo_constrained | MVO with explicit IPS box constraints + risk-aversion λ | | tpa | Total Portfolio Allocation: regime-tilted risk parity |

Constraint projection

After every optimiser, weights are projected onto the IPS feasible set with the exact Euclidean bounded-simplex projection (utils.project_to_box). Solve the Lagrange multiplier by monotone bisection. Reject the IPS before optimization when sum(min_w) > 1 or sum(max_w) < 1; never return an almost-feasible vector.

CLI

python skills/portfolio-construction/scripts/run_all.py \
       --cmas outputs/demo01/cmas.json \
       --cov  outputs/demo01/covariance.json \
       --ips  ips/ips_template.md \
       --out  outputs/demo01/pc_proposals.json

Run through pipeline/orchestrator.py for schema gating and governed output.

Source & license

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

Author: nutdnuy
Source: nutdnuy/self-driving-portfolio-skill
License: MIT

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

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Versions

v0.1.0 Imported from the upstream source.