PyPI Stats
hudson-and-thames

arbitragelab

ArbitrageLab is a collection of algorithms from the best academic journals and graduate-level textbooks, which focuses on the branch of statistical arbitrage known as pairs trading. We have extended the implementations to include the latest methods that trade a portfolio of n-assets (mean-reverting portfolios).
PyPI GitHub
Downloads
Day
145
Week
409
Month
896
Stars
653
Forks
214
Issues
4
Version
1.0.0

Package Insights

What's this?
Score breakdown - each component scores 0–100, weighted by percentage
Maintenance
10
Popularity
62
Adoption
29
Community
50
How the maintenance status was determined
Last commit
724 days ago
Monthly downloads
896
Active
Activity within 30 days
Stable
Activity within 31-180 days
• Minimal
Activity within 181-365 days, or no activity data
At Risk
No activity for > 365 days, but > 10,000 monthly downloads
Archived
Repository flagged as archived on GitHub
How the popularity category was determined
Monthly downloads
896
Stars
653
Stars per 1k downloads
728.79
Industry Standard
> 10,000,000 monthly downloads
Hidden Gem
< 0.5 stars per 1k downloads and > 100,000 monthly downloads
Community Favorite
> 5 stars per 1k downloads
Rising Star
Balanced ratio of stars to downloads
• Unknown
Fewer than 1,000 monthly downloads, or no star data
Needs at least 1,000 monthly downloads to classify popularity.
How download momentum is calculated
Week daily avg
58
Month daily avg
30
Momentum
—
((week_daily_avg - month_daily_avg) / month_daily_avg) * 100
Momentum not reported for packages with < 5,000 monthly downloads — percentages are noisy at low volume.
Python version support tiers
requires_python
<4.0,>=3.8
Cutting Edge
Minimum supported version is 3.12 or newer
Modern
Minimum supported version is 3.9, 3.10, or 3.11
• Legacy
Supports 3.8 or older (or Python 2)
Unknown
No requires_python specified or unparseable
License categories
License
BSD-3-Clause
• Permissive
MIT, Apache, BSD, ISC, Unlicense, CC0, etc.
Copyleft
GPL, LGPL, AGPL, MPL, EPL, etc.
Proprietary
Commercial, all rights reserved, custom EULAs
Unknown
No license specified, or none of the above match
How the release cadence was determined
Last release
724 days ago
Total releases
2
Releases/year
1.0
Rapid
Last release within 365 days and > 12 releases/year
Regular
Last release within 365 days
• Slow
Last release 366-730 days ago
Stalled
Last release > 730 days ago, or no releases
Unknown
No usable release date available
How contributor risk was determined
Contributors
7
Monthly downloads
896
High Load
≤ 2 contributors and ≥ 50,000 monthly downloads
Moderate Load
< 10 contributors and ≥ 500,000 monthly downloads
Low Load
< 25 contributors and ≥ 5,000,000 monthly downloads, or sole maintainer with ≥ 10,000 monthly downloads
• Balanced
Enough contributors for the package's popularity
Unknown
No contributor data available
Engagement
52
 
Issue Burden
6.1
per 1k stars
Discussions
0.0
per 1k stars
Fork Ratio
3.3%
contrib / forks
Stale Release
No
 
PR Velocity
Quiet
 

Weekly Downloads

GitHub Stars

Not all downloads include detailed metadata. Breakdowns reflect the subset that does.

Downloads by OS

Linux 33

Python Versions

3.11
97.0% 32
3.12
3.0% 1

Top Countries

1. US US
33
2. CA CA
1
3. GB GB
1
4. IN IN
1

Dependencies

29

Used By

0
Not used by any tracked packages

Package Information

License
BSD-3-Clause
First Release
April 15, 2024
Last Release
1 year ago
Last Commit
1 year ago
Latest Version
1.0.0
Total Releases
2
Contributors
7
Open PRs
3
Archived
No
Author
Hudson and Thames Quantitative Research
Python Versions
3 3.8 3.9 3.10 3.11 3.12
Wheels
py3
Keywords
arbitrage finance investment education trading
Topics
-
Tracking Since
January 14, 2026
Data Updated
May 3, 2026
Data Freshness
Fresh

Links