Datasetpublic

CyberMax-tools/riskroll-sec-10k-10q-sections

Riskroll: SEC 10-K and 10-Q sections as clean text Need it fresh, filtered or via API? This free file is a snapshot (10-K/10-Q sections up to the last refresh), last updated 2026-09-24. Insidewell on Apify ($0.004 per insider transaction): pulls today's SEC Form 4 trades for your own watchlist, filtered by buy/sell and size, with cluster-buy alerts on a schedule. Using it at work? Commercial license + support (from $49/year): invoice, PDF licence certificate, named… See the full description on the dataset page: https://huggingface.co/datasets/CyberMax-tools/riskroll-sec-10k-10q-sections.

sourceHugging Facecc0-1.0updated 4h agoView on Hugging Face

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Riskroll: SEC 10-K and 10-Q sections as clean text

Need it fresh, filtered or via API? This free file is a snapshot (10-K/10-Q sections up to the last refresh), last updated 2026-09-24. - [Insidewell on Apify](https://data.cybermaxtools.com/buy/insidewell?s=hf-riskroll-sec-10k-10q-sections) ($0.004 per insider transaction): pulls today's SEC Form 4 trades for your own watchlist, filtered by buy/sell and size, with cluster-buy alerts on a schedule. - Using it at work? [Commercial license + support](https://data.cybermaxtools.com/buy/dataset-license?s=hf-riskroll-sec-10k-10q-sections) (from $49/year): invoice, PDF licence certificate, named support, freshness and availability commitments and an SLA; the data stays free and open for everyone. - [Get an email when this dataset updates](https://data.cybermaxtools.com/notify?ds=riskroll-sec-10k-10q-sections&s=hf-riskroll-sec-10k-10q-sections): free, double opt-in, unsubscribe any time. - [CyberMax Store](https://cybermaxtools.com/store/?utm_source=huggingface&utm_medium=dataset&utm_campaign=riskroll-sec-10k-10q-sections): every CyberMax data product, API plan and weekly brief in one place. Information only, not investment advice.

The parts of annual and quarterly reports that analysts, researchers and LLM pipelines actually read, cut out of each filing and cleaned: Risk Factors (Item 1A), Management's Discussion and Analysis (MD&A), Quantitative and Qualitative Disclosures About Market Risk, Cybersecurity (Item 1C) and Business (Item 1), one row per filing × section, for every 10-K and 10-Q filed with the SEC. New filings are added as they come in, so the corpus grows month by month.

This build (see meta.json): 2,098 filings (10-K, 10-Q and amendments) filed 2026-08-12 to 2026-09-23 (plus one filing dated 2026-02-23 that EDGAR indexed in September; 1,858 10-Q, 170 10-K, 67 amendments, 3 transition reports; the tail of the Q2 10-Q season plus fiscal-June annual reports), 5,245 sections: 1,886 MD&A, 1,560 Risk Factors, 1,441 Market Risk, 185 Business and 173 Cybersecurity, 20.4 million words in total. 1,979 of the filings have at least one section (Part III-only amendments and exhibit-only filings have none, by design; 63 filings from the 12–14 Aug peak couldn't be fetched because SEC was throttling and are marked sec_fetch_failed; see filings).

Why this and not the popular EDGAR corpora? The best-known 10-K section corpus on Hugging Face (EDGAR-CORPUS) was last updated in July 2023 and has annual reports only; full-filing dumps leave the section splitting to you. This one starts with 2026 filings, includes 10-Qs (quarterly MD&A and risk-factor updates) and the new Item 1C cybersecurity disclosures, and keeps adding filings.

Use it

python

from datasets import load_dataset
ds = load_dataset("CyberMax-tools/riskroll-sec-10k-10q-sections", "sections", split="train")

# Every risk-factor section that mentions tariffs
risky = ds.filter(lambda r: r["section"] == "risk_factors" and "tariff" in r["text"].lower())
print(len(risky), risky[0]["company_name"], risky[0]["filing_url"])

DuckDB, straight from the Hub:

sql

SELECT ticker, company_name, form_type, filed_date, n_words
FROM 'hf://datasets/CyberMax-tools/riskroll-sec-10k-10q-sections/data/sections-*.parquet'
WHERE section = 'cybersecurity' ORDER BY n_words DESC LIMIT 20;

Good for: RAG over company filings, risk-factor change tracking (compare a company's 10-K with its next 10-Qs), classifier and summarizer training/evaluation, sector-wide risk themes (AI, tariffs, cyber incidents, rates), and giving an AI agent the "why" behind the numbers.

Configs and columns

`sections` (default, one row per filing × section): accession_number, form_type, filed_date, period_of_report, cik, ticker, company_name, section (risk_factors, mdna, market_risk, cybersecurity, business), item (1A, 7, 7A, 1C, 1 for 10-K; II-1A, I-2, I-3 for 10-Q), text, n_chars, n_words, filing_url (EDGAR index page), document_url (the primary document the text came from).

`filings` (one row per 10-K/10-Q filing in the window): the same identifiers plus sections_found and status (ok, no_sections_found, no_html_primary_document, sec_fetch_failed), so you can see exactly what was and wasn't extracted.

How the text is made: the filing's primary HTML document is converted to text line by line (tables kept as cell | cell rows, page numbers and "Table of Contents" lines dropped). A section runs from its Item heading to the next Item heading; when a heading appears more than once (table of contents, cross-references), the occurrence with the longest body is used. Nothing is paraphrased or summarized. Smaller reporting companies often write "not required" under Market Risk; those short sections are kept as filed. Parsing is heuristic, so a small share of filings with unusual layouts can have a section missing or cut early; check document_url when it matters.

Refresh

New filings are added weekly from the SEC's daily indexes; files are per filing month (data/sections-YYYY-MM.parquet). meta.json has the latest build's window and counts.

Licence

SEC EDGAR filings are US government public records, free of copyright restrictions; this compilation is released under CC0 1.0. Compiled by CyberMax. Not affiliated with or endorsed by the SEC. Not investment advice.

Also from CyberMax

—Insidewell: SEC Form 4 insider trading tracker: insider buys and sells for any watchlist of tickers, with cluster-buy flags, on demand or on a schedule, callable by AI agents over MCP.
—Free dataset: Figurewell: SEC XBRL financial statements and key metrics, the numbers for the same companies (join on accession_number = adsh, or on ticker).
—Free dataset: Eventwren: SEC 8-K material events by Item.
—Free dataset: SEC Form 4 insider transactions, latest 5 EDGAR days.
—More tools for AI agents and data teams: https://apify.com/cybermax

More free from CyberMax

—All free CyberMax demos & datasets
—Figurewell: SEC XBRL Financial Statements & Key Metrics (every US filer, latest 4 quarters)
—Eventwren: SEC 8-K Material Events by Item (latest EDGAR filings)
—Insidewell: SEC Insider Trades

Quickstart notebook

Load this dataset with pandas and see real outputs in the quickstart notebook.