factor-research-multiple-testing-correction SKILL.md skillA
factor-research-multiple-testing-correction from himanshuj16/algo-trading-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add himanshuj16/algo-trading-skills/factor-research-multiple-testing-correction@v1.1.0Pins v1.1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- himanshuj16/algo-trading-skills
- Path
skills/factor-research-multiple-testing-correction/SKILL.md- Versions recorded
- 5
- Latest version
- v1.1.0, committed Sep 4, 2026
- First version recorded
- Jul 30, 2026
- Size
- 9,635 bytes
- Repository stars
- 50
- License
- Apache-2.0
Use when a research pipeline screens many candidate factors and selection rests on t-statistics or p-values. Bonferroni and Holm bound family-wise error; Benjamini-Hochberg and BHY bound false discovery rate under dependence; plus the Harvey-Liu-Zhu t-hurdle.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
## When to Use Use this skill when a research pipeline screens more than one candidate factor and the selection decision rests on t-statistics or p-values: factor discovery sweeps, signal libraries, parameter grids evaluated as separate hypotheses, and any promotion gate where "it was significant in the backtest" is the argument for going live. Screening $M$ candidates at the single-test cutoff ($p \le 0.05$, $|t| \ge 1.96$) is expected to produce $0.05 \times M$ significant results from pure noise — 50 of them out of 1,000. Harvey, Liu and Zhu (2016) argue this is exactly how the published factor zoo was assembled, and recommend that a newly discovered factor clear $|t| \ge 3.0$. ## When NOT to Use - **A single pre-registered hypothesis.** With $M = 1$ every procedure here collapses to the raw p-value; the correction adds nothing. - **As a fix for a broken backtest.** These are statistical corrections. They cannot see look-ahead leakage, a survivorship-biased universe, or overlapping-return t-statistic inflation. A corrected t-statistic on a leaked signal is still leaked — see `lookahead-bias-elimination`. …
Read the whole file at its exact version.
How to install
mdr add himanshuj16/algo-trading-skills/factor-research-multiple-testing-correction@sha256:a27af71f246ab332The line at the top of this page pins the label v1.1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_2oyvvdzg5r7haakn)
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Versions
The registry has recorded 5 versions of this file, between Jul 30, 2026 and Sep 4, 2026, about one every 9 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.1.0 latest | 2026-09-04 | d466d60 | 9,635 B | A | view · diff |
| v1.1.0 | 2026-09-03 | 8527a51 | 9,576 B | A | view · diff |
| v1.1.0 | 2026-08-25 | 7e72405 | 9,690 B | A | view · diff |
| v1.0.0 | 2026-07-30 | 92ed2bc | 3,615 B | A | view · diff |
| v1.0.0 | 2026-07-30 | dfc60c7 | 624 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 (9635 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
himanshuj16/algo-trading-skills · 50 stars · license Apache-2.0 · pushed 2026-09-14 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_2oyvvdzg5r7haakn GET https://markdownregistry.com/api/v1/resolve?ref=himanshuj16/algo-trading-skills/factor-research-multiple-testing-correction GET https://markdownregistry.com/api/v1/blob/a27af71f246ab33269de0766177f6644ecc2d17866dbfa18e6176ed7656efb9c
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.