SKILL verified MIT Self-run

Covariance

Name: Covariance
Availability: InStock
Author: nutdnuy

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

This skill should be used when the user asks to "estimate a covariance matrix", "run Ledoit-Wolf shrinkage", "build an EWMA covariance", or validate PSD risk inputs for portfolio construction.

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Install

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

✓ 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

✓ Security review passed

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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.

Preview Execution monitoring

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About

covariance

Covariance estimation for the SAA pipeline.

Methods

| method | Description | | --------------- | --- | | sample | Plain MLE; use only when T ≫ N. | | ewma | Exponentially-weighted, λ=0.94 (RiskMetrics-style). | | ledoit_wolf | Linear shrinkage toward a constant-correlation target. Default. |

All matrices are returned annualised (×252 for daily inputs).

Require at least 60 complete aligned return rows. Symmetrise each estimate and clip non-positive eigenvalues to a scale-aware floor. Record the original minimum eigenvalue, repair flag, condition number, aligned sample size, and missing-data fraction. Treat repair as numerical stabilization, not economic validation.

CLI

python skills/covariance/scripts/build_cov.py \
       --tickers SPY,EFA,EEM,IEF,LQD,TIP,GLD,VNQ,BIL \
       --method ledoit_wolf \
       --as-of 2026-05-08 \
       --out outputs/demo01/covariance.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.