Professional-grade SEC financial data for financial analysts, quantitative researchers, data engineers, and investment teams.
This repository serves as the official integration hub for Valuein Financial Data Essentials feed by hosting our documentation, features requests, issue tracker, and the official Python SDK, schema definitions, and usage patterns for production environments.
- Data Dictionary: The live, auto-updated definition of every metric and column.
- Connection Guide: How to connect via Snowflake, Postgres, or API.
- Schema Guide: Entity-relationship diagrams and join logic.
We adhere to strict standards to ensure institutional-grade reliability.
- Methodology: How we map GAAP/IFRS tags to standardized metrics and handle restatements.
- SLA Policy: Our commitment to 99.9% uptime and <2min SEC filing latency.
- Restatement Handling: We preserve "as-reported" history to support true point-in-time backtesting.
Clone this repo and install dependencies:
git clone [https://github.com/valuein/quants.git](https://github.com/valuein/quants.git)
cd quants
pip install -r requirements.txtWe provide tailored examples for different roles:
| Role | Directory | Use Case |
|---|---|---|
| Data Engineers | examples/01_engineering |
Bulk ingestion, schema validation, incremental loading. |
| Quants | examples/02_quantitative |
Alpha factor creation, time-series alignment, backtesting. |
| Analysts/PMs | examples/03_fundamental |
DCF modeling inputs, peer comparison, ratio analysis. |
- Found a data error? Open a Data Ticket
- Need a new metric? Request a Feature
- Service down? Service Outage
- General Question? Start a Discussion
This project is licensed under a Proprietary Software License. See the LICENSE file for more information.