Categorical features and cross-sectional neutralization
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enhancement
- Dominant language
- Python
- Stars
- 48.7k
- Forks
- 7.7k
- PR merge metrics
- No merged PRs in 30d
Description
- The feature bin files only support float data now, but sometimes we need to dump categorical or string features(like industry or sector) into the feature bin files.
- Cross-sectional neutralization is a widely used data processor in equity quant investment. Maybe you should consider adding a neutralization processor, with which we can neutralize the data on sector, size or beta.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points. Start by locating the feature bin handling and data processor interfaces, then determine whether categorical feature storage and cross-sectional neutralization can be scoped separately. Done means both requested capabilities have defined behavior and coverage for their supported inputs.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, fintech-quant
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100