correlation-analysis skillA
correlation-analysis is agent-read markdown (skill) from hkuds/vibe-trading: Correlation and cointegration analysis — co-movement discovery, deep return-correlation analysis, sector clustering, realized correlation, Engle-Granger / Johansen cointegration, half-life, Kalman dynamic hedge ratio, cross-market linkage analysis, and pair-trading signal generation.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified before it reaches your agent: the main file against the SHA-256 recorded here, the others against the git hashes of its source commit. The deterministic audit below grades the latest version, and the same checks always give the same file the same grade.
What the file says
# Correlation and Cointegration Analysis ## Overview Correlation analysis is a foundational tool for pairs trading, portfolio construction, and risk management. This skill covers four analysis modes (co-movement discovery / return-correlation deep dive / sector clustering / realized correlation), a full cointegration-testing framework, cross-market linkage analysis, and the complete workflow from analytics to pair-trading signals. --- ## Mode 1: Co-Movement Discovery **Use case**: Given a target asset, scan a universe for highly correlated assets and build a candidate pool with similar industry or factor exposure, for use in pairs trading or substitute identification. ### Workflow ``` 1. Pull daily return series for the target asset and N candidates 2. Compute Pearson / Spearman correlations between the target and each candidate 3. Rank by correlation in descending order and keep Top-K (usually K=10-20) 4. Run cointegration tests on the Top-K set to retain pairs with real long-run equilibrium 5. Output the candidate pool and a correlation summary ``` ```python import pandas as pd import numpy as np from scipy.stats import pearsonr, spearmanr def scan_correlated_assets( …
Read the whole file at its exact version.
How to install
mdr add hkuds/vibe-trading/correlation-analysis@git:20260911.bd29a18mdr add hkuds/vibe-trading/correlation-analysis@sha256:ef15489b70479c78Pin to a label to follow the author's releases, or to a sha256 for exact bytes. Either way the resolved hash is written to mdr.lock, and mdr install fetches those bytes again and checks them, so it installs them exactly or fails.
[](https://markdownregistry.com/a/art_tkgzpittwtixtl5p)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260911.bd29a18 latest | 2026-09-11 | bd29a18 | 40,259 B | A | view · diff |
| git:20260910.511e224 | 2026-09-10 | 511e224 | 40,338 B | A | view · diff |
| git:20260908.be2c09f | 2026-09-08 | be2c09f | 40,328 B | A | view · diff |
| git:20260621.4a64f0e | 2026-06-21 | 4a64f0e | 40,248 B | A | view · diff |
| git:20260409.27354eb | 2026-04-09 | 27354eb | 39,068 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (40259 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
hkuds/vibe-trading · 34,089 stars · license MIT · pushed 2026-09-27 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_tkgzpittwtixtl5p GET https://markdownregistry.com/api/v1/resolve?ref=hkuds/vibe-trading/correlation-analysis GET https://markdownregistry.com/api/v1/blob/ef15489b70479c7850c302c64b3a53b835495e957863f6b14bcbe3df33c97e08
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