CNBC Research Notebook

[Ruuudy1]

matches main.py

notebook templates; this one is a bit different as the dataset for our universe is always a value of 1 ( buycount and totalmentions are usually just one since our universe is strict BUY >= 3) so instead I plotted the number of unique assets added to the universe over a 120 day universe_history request. Then I plotted a bar chart of standard error and violin plots to show meaningful statistics.

Description

• https://www.quantconnect.cloud/backtest/f9a27c45fd03371b337bd7d31aaf92ad/?theme=darkly
• https://github.com/QuantConnect/Documentation/blob/master/project-templates/python/alternative-data-universe-quivercnbcsuniverse/main.py

Related Issue

N/A

Motivation and Context

Context our Assistants

Types of changes

• Bug fix (non-breaking change which fixes an issue)
• Refactor (non-breaking change which improves implementation)
• New feature (non-breaking change which adds functionality)
• Non-functional change (xml comments/documentation/etc)

Checklist:

• My code follows the code style of this project.
• I have read the CONTRIBUTING document.
• My branch follows the naming convention bug-<issue#>-<description> or feature-<issue#>-<description>