What is AssayingAnomalies?
AssayingAnomalies is a pypi that This library is a Python implementation of the MATLAB Toolkit that accompanies Novy-Marx and Velikov (2023) and is to be used for empirical academic asset pricing research, particularly focused on stu. It has a Nerq Trust Score of 48/100 (D). 0 GitHub stars. Published by Joshua Lawson. Last analyzed September 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 0/100 — Maintenance activity is low
- ⚠️ Community: 0 stars, 0 downloads — Growing community
- ⚠️ Transparency: License: Not specified — No license specified
Trust & Safety Overview
What AssayingAnomalies Does
AssayingAnomalies is a pypi in the pypi category. This library is a Python implementation of the MATLAB Toolkit that accompanies Novy-Marx and Velikov (2023) and is to be used for empirical academic asset pricing research, particularly focused on studying anomalies in the cross-section of stock returns.. It is published by Joshua Lawson and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use AssayingAnomalies
AssayingAnomalies is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.
Details
| Author | Joshua Lawson |
|---|---|
| Category | pypi |
| License | Not specified |
| Type | pypi |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 0/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=assayinganomalies
Setup guide · Full safety report · Production review · Is it safe?
Frequently Asked Questions
Last updated September 2026. Trust scores based on automated analysis of public data.