Alternative data datasets
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Records of SEC audit fee disclosures covering the period from 2004 through 2009.
Records of SEC audit fee disclosures spanning the years 2004 to 2024.
Records of SEC audit fee disclosures covering the period from 2010 to 2014.
Records of SEC audit fee disclosures covering the period from 2015 to 2019.
Records of SEC audit fee disclosures covering the period from 2020 to 2024.
A standardized disclosure platform aggregating climate, water and forestry reporting from over 23,000 corporations and public bodies, covering emissions, targets, risks and consumption.
A sustainability disclosures feed offering more than 450 detailed ESG and emissions-related data points.
View source information and access options.
View source information and access options.
View source information and access options.
Tracks FDAAA Section 801 reporting adherence, ranks sponsor credibility, and surfaces trial-level risk signals.
An open, layout-preserving conversion of U.S. SEC EDGAR filings into MultiMarkdown format covers approximately 3.4 million documents submitted between January 2022 and June 2025, designed for long-context language modeling, financial reasoning, and document analysis.
Risk and compliance intelligence derived from official audit and supervisory examination records applied across regulated organizations.
An anonymized consumer purchase dataset from Bloomberg Second Measure that projects corporate revenue ahead of official disclosures.
Disclosure documents submitted by institutional investment firms that manage portfolios exceeding $100 million under Section 13(f).
Automated language processing system that mines corporate disclosures for causal statements and forward-looking commentary.
Millions of consumer complaints about financial products, mortgages, credit cards, debt collection and loans, with product, issue, company response and ZIP-level geography, together with HMDA mortgage disclosures.
Mechanical Utility Patents — 100 HTML Records A curated collection of 100 distinct granted U.S. utility patents from 100 patent families, saved as HTML for mechanical-engineering document analysis. Published by cmuchancel. Source disclosure: the patent text, bibliographic metadata, and drawings were obtained from Google Patents. Original PDFs and drawing assets are hosted on patentimages.storage.g
Compensation benchmarks for executives and staff assembled from proxy disclosures filed by publicly traded companies.
A corpus of SEC EDGAR filings in English (Apache 2.0), roughly a few hundred thousand company documents including annual and quarterly reports and exhibits. The filings text is organized for model pretraining and retrieval, but the same documents are the raw material for filings-based and disclosure signals.
Information on the decarbonization plans and progress of more than 45,000 firms over an eleven-year span.
A dataset providing sustainability ratings for thousands of global firms, intended to support investor analysis of corporate environmental and social impact.
A measure of how individual companies address the most relevant environmental, social, and governance challenges facing their industries.
A benchmark of corporate performance against the ESG issues that are most financially material under prevailing market conditions.
Unprocessed ESG indicator values for more than four hundred companies included in the NASDAQ benchmark index.
A dataset from ESG Book supplying firm-level sustainability indicators aligned with the Sustainable Finance Disclosure Regulation's reporting requirements.
Data from legally mandated personal finance disclosure documents
Text of IPO filings, including S-1 and related prospectuses, in JSON: hundreds of thousands of records in English (CC BY 4.0). Pre-IPO disclosure text is one of the few information sources available ahead of a listing.
Reporting package designed to support compliance with EU Taxonomy requirements for ESG-related disclosures.
Worldwide business-entity and firmographic records consolidating corporate registries, ownership hierarchies and contact details.
Corporate and sovereign-level information supporting SFDR compliance regarding Principal Adverse Impact disclosures.
A consolidated, ready-to-use repository of 13F institutional holdings drawn from SEC EDGAR filings, capturing the most recent quarterly disclosures of more than 13,000 investment managers including hedge funds, mutual fund complexes, pension funds, banks, and family offices, with each record summarizing total assets under management and individual positions.
10-K filings for S&P 500 companies retrieved from EDGAR, stored as Parquet with the filing text attached (MIT). A focused corpus for the large-cap annual disclosure cycle: risk factors, MD&A and segment detail for every S&P 500 name.
An assessment tool that measures how well ESG disclosures align with CSRD reporting requirements.
Entertainment industry datasets, music-streaming subscriber counts, video, gaming and creator-economy metrics, assembled from disclosures and web measurement.
Complete filing metadata and URLs for all 8-K material event disclosures in Q4
Complete textual SEC 10-K annual filings from 2021, suited for studying corporate disclosures and natural language processing tasks.
sec-filings is a Hugging Face dataset published by Sicheng-Chroma that distributes pre-chunked U.S. SEC filings paired with dense vector embeddings. It is distributed in optimized Parquet format and is intended for retrieval and similarity research over regulatory disclosures.
10-K annual filings from EDGAR in Parquet, tens of thousands of documents. The standard annual-disclosure corpus for fundamentals, risk-factor and management-discussion analysis.
Normalized stock-trade disclosures filed by U.S. House and Senate members under the STOCK Act, regenerated on a schedule by the repository's own pipeline rather than curated manually.
ZipLime US Insider Trading Disclosures (PIT) [!CAUTION] Use knowledge_date, not transaction_date, when backtesting. transaction_date says when a trade occurred; knowledge_date says when the filing became observable through EDGAR. Using the former as the signal date introduces look-ahead bias. visible = trades.filter(pl.col("knowledge_date") <= simulation_time) This dataset normalizes corporate-ins