Open Finance Society

Welcome to the OpenQuant research & data platform

OpenQuant is a research and data platform for financial and investment analysis. We aggregate publicly available datasets, including SEC filings and macroeconomic data, and pair them with practical analysis tools. From a filing viewer and data discovery to reproducible notebooks and regression analysis, OpenQuant helps turn raw information into clear, testable insights.

Change log

  • 2025-11-04

    • Fundamental tab in Company webpage is up now, and enables multi-filing time-series analysis, based on fiscal-to-calendar and CQ-to-Q standardization & inference. Data item covers statement+segment+note, including company-specific items (1000+ for a complex filing like DUK). This mounts to million-level quarterly data points for 2022-202510, well beyond Yahoo Finance's item coverage.
    • This fundamental data is also available in SQL Studio, see demo query there. If your browser can't find it, it could be a cache issue, please press the "Clear Cache" button.
    • SQL Studio now supports sec corp filing ref data (10-K/Q, 8-K, 20-F, 40-F) for 2022-202510, and sec all filing (corp, person, fund/trust) ref data for 2025 only as poc. Demo query updated.
    • Filing tab in Company webpage supports all-XBRL extracted data + raw filing for ~500 stocks, as a starting point for quantamental workflow.
    • Front-end improvement: expand Service Worker and OPFS cache usage. Added clear-cache button to actively manage cache. If you can't access certain new file, or suspect content is stale, please clear cache.

  • 2025-10-20

    • SQL Studio: poc for new sec ref data
    • Front-end improvement: better handling of data file cache, SEO-friendly minor change.

  • 2025-10-18

    • A blog to explain why cooking oil gets caught up in US-China trade tension and its relation with clean energy.

Tools

  • SQL Studio: low-code query equity+macro data in-browser (DuckDB SQL).

  • Company: filing-driven fundamental analysis (based on FASB XBRL standardized accounting data) and stock price chart.

  • Industry: industry-specific datasets.

  • Geospatial: a bit of geo flavor using maritime data.

  • Macro: macro time-series plotting and Fed.

  • Python Lab: JupyterLite with a code-less treasury fair value model demo. It runs in your browser, no installation required.

  • Blog: notes on the technical and non-technical aspects of OpenQuant.

Data and workflow design viewpoint

  • Human + LLM ready: We prepare data so it’s consistently usable by people and large language models alike.

  • Structured + unstructured: We combine structured and unstructured sources, take into account time dimension, and derive insights from it.

  • Quantamental by design: Built to support both discretionary and systematic workflows.

Disclaimer

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