The data sets below provide selected information extracted from exhibits to corporate financial reports filed with the Commission using eXtensible Business Reporting Language (XBRL).

This dataset is from the SEC's Financial Statements and Notes Data Set.
It was a personal project to see if I could make the queries efficient.
It's just been collecting dust ever since, maybe someone will make good use of it.
Data is up to about early-2024.
It doesn't differ from the source, other than it's compiled - so maybe you can try it out, then compile your own (with the link below).
Dataset was created using SEC Files and SQL Server on Docker.
For details on the SQL Server database this came from, see: "dataset-previous-life-info" folder, which will contain: - Row Counts - Primary/Foreign Keys - SQL Statements to recreate database tables - Example queries on how to join the data tables. - A pretty picture of the table associations. Source: https://www.sec.gov/data-research/financial-statement-notes-data-sets

Happy coding!

Korean Companies’ Financial Data provides important information to analyze a company’s financial status and performance. This data includes financial indicators such as revenue, expenses, assets, and liabilities. Collected from corporate financial reports and stock market data, it helps investors evaluate financial health and discover investment opportunities, essential for valuing Korean companies.

The Financial Statements of Holding Companies (FR Y-9 Reports) collects standardized financial statements from domestic holding companies (HCs). This is pursuant to the Bank Holding Company Act of 1956, as amended (BHC Act), and the Home Owners Loan Act (HOLA). The FR Y-9C is used to identify emerging financial risks and monitor the safety and soundness of HC operations. HCs file the FR Y-9C and FR Y-9LP quarterly, the FR Y-9SP semiannually, the FR Y-9ES annually, and the FR Y-9CS on a schedule that is determined when this supplement is used.

Our Financial API provides access to a vast collection of historical financial statements for over 50,000+ companies listed on major exchanges. With this powerful tool, you can easily retrieve balance sheets, income statements, and cash flow statements for any company in our extensive database. Stay informed about the financial health of various organizations and make data-driven decisions with confidence. Our API is designed to deliver accurate and up-to-date financial information, enabling you to gain valuable insights and streamline your analysis process. Experience the convenience and reliability of our company financial API today.

In the U.S. public companies, certain insiders and broker-dealers are required to regularly file with the SEC. The SEC makes this data available online for anybody to view and use via their Electronic Data Gathering, Analysis, and Retrieval (EDGAR) database. The SEC updates this data every quarter going back to January, 2009. For more information please see this site.

To aid analysis a quick summary view of the data has been created that is not available in the original dataset. The quick summary view pulls together signals into a single table that otherwise would have to be joined from multiple tables and enables a more streamlined user experience.

DISCLAIMER: The Financial Statement and Notes Data Sets contain information derived from structured data filed with the Commission by individual registrants as well as Commission-generated filing identifiers. Because the data sets are derived from information provided by individual registrants, we cannot guarantee the accuracy of the data sets. In addition, it is possible inaccuracies or other errors were introduced into the data sets during the process of extracting the data and compiling the data sets. Finally, the data sets do not reflect all available information, including certain metadata associated with Commission filings. The data sets are intended to assist the public in analyzing data contained in Commission filings; however, they are not a substitute for such filings. Investors should review the full Commission filings before making any investment decision.

Annual reports Assessment Dataset

This dataset will help investors, merchant bankers, credit rating agencies, and the community of equity research analysts explore annual reports in a more automated way, saving them time.

Following Sub Dataset(s) are there :

a) pdf and corresponding OCR text of 100 Indian annual reports These 100 annual reports are for the 100 largest companies listed on the Bombay Stock Exchange. The total number of words in OCRed text is 12.25 million.

b) A Few Examples of Sentences with Corresponding Classes The author defined 16 widely used topics used in the investment community as classes like:

Accounting Standards

Accounting for Revenue Recognition

Corporate Social Responsbility

Credit Ratings

Diversity Equity and Inclusion

Electronic Voting

Environment and Sustainability

Hedging Strategy

Intellectual Property Infringement Risk

Litigation Risk

Order Book

Related Party Transaction

Remuneration

Research and Development

Talent Management

Whistle Blower Policy

These classes should help generate ideas and investment decisions, as well as identify red flags and early warning signs of trouble when everything appears to be proceeding smoothly.

ABOUT DATA ::

"scrips.json" is a json with name of companies "SC_CODE" is BSE Scrip Id "SC_NAME" is Listed Companies Name "NET_TURNOV" is Turnover on the day of consideration

"source_pdf" is folder containing both PDF and OCR Output from Tesseract "raw_pdf.zip" contains raw PDF and it can be used to try another OCR. "ocr.zip" contains json file (annual_report_content.json) containing OCR text for each pdf. "annual_report_content.json" is an array of 100 elements and each element is having two keys "file_name" and "content"

"classif_data_rank_freezed.json" is used for evaluation of results contains "sentence" and corresponding "class"

Company fundamentals data provides the user with a company's current financial health and when combined historically, the financial 'life-story' of the company.

The Corporate Financial Fraud project is a study of company and top-executive characteristics of firms that ultimately violated Securities and Exchange Commission (SEC) financial accounting and securities fraud provisions compared to a sample of public companies that did not. The fraud firm sample was identified through systematic review of SEC accounting enforcement releases from 2005-2010, which included administrative and civil actions, and referrals for criminal prosecution that were identified through mentions in enforcement release, indictments, and news searches. The non-fraud firms were randomly selected from among nearly 10,000 US public companies censused and active during at least one year between 2005-2010 in Standard and Poor's Compustat data. The Company and Top-Executive (CEO) databases combine information from numerous publicly available sources, many in raw form that were hand-coded (e.g., for fraud firms: Accounting and Auditing Enforcement Releases (AAER) enforcement releases, investigation summaries, SEC-filed complaints, litigation proceedings and case outcomes). Financial and structural information on companies for the year leading up to the financial fraud (or around year 2000 for non-fraud firms) was collected from Compustat financial statement data on Form 10-Ks, and supplemented by hand-collected data from original company 10-Ks, proxy statements, or other financial reports accessed via Electronic Data Gathering, Analysis, and Retrieval (EDGAR), SEC's data-gathering search tool. For CEOs, data on personal background characteristics were collected from Execucomp and BoardEx databases, supplemented by hand-collection from proxy-statement biographies.

Comprehensive database of over 100,000 financial filings from 8,000+ European companies

Browse LSEG's US Company Filings Database, and find a range of filings content and history including annual reports, municipal bonds, and more.

Custommade Historical Financial Data For 230M Companies Worldwide: - Data from 2017, 2018, 2019, 2020 & 2021 - Includes turnover, employee size. - Custommade based on geographical location, turnover range, employee range and industry type - Standardized database for all countries

Make data work for you. With unbeatable data, skilled data experts and smart technology, we help businesses to unlock the power of international data.

The Financial Statements of U.S. Nonbank Subsidiaries of U.S. Holding Companies (FR Y-11; FR Y-11S) reporting forms collect financial information for individual nonfunctional regulated U.S. nonbank subsidiaries of domestic holding companies, which is essential for monitoring the subsidiaries' potential impact on the condition of the holding company or its subsidiary banks. Holding companies file the FR Y-11 on a quarterly or annual basis or the FR Y-11S on an annual basis, predominantly based on whether the organization meets certain asset size thresholds. The FR Y-11 data are used with other holding company data to assess the condition of holding companies that are heavily engaged in nonbanking activities and to monitor the volume, nature, and condition of their nonbanking operations.

The number of shares outstanding, shown on a company’s balance sheet under the heading “capital stock” is used to calculate key metrics including market capitalization figures, earnings per share (EPS) and share stakes for regulatory reporting levels. The Share Outstanding service consists of two datasets, Official Shares Outstanding and Daily-Adjusted Shares Outstanding.

Official Shares Outstanding Providing official figures sourced directly from local exchanges or company sources, as soon as they are published. The frequency of official updates varies from market to market. Updates can also range from daily to annually.

Adjusted Share Outstanding When corporate actions occur prior to the release of official updates, the number of shares outstanding can be impacted drastically. Use the adjusted shares outstanding dataset to provide the figures for events including:
Bonus Bonus rights Buyback Capital Reduction Consolidation Conversion Demerger Divestment Entitlement Redemption Rights Sub-division

Once the official figures have been released by the exchange, then receive reverted figures. The Worldwide Shares Outstanding service provides up-to-date figures from over 100 countries worldwide enabling companies to efficiently calculate figures to comply with exchange regulations or portfolio holding levels.

This dataset builds upon "Financial Statement Data Sets" by incorporating several key improvements to enhance the accuracy and usability of US-GAAP financial data from SEC filings of U.S. exchange-listed companies. Drawing on submissions from January 2009 onward, the enhanced dataset aims to provide analysts with a cleaner, more consistent dataset by addressing common challenges found in the original data.

Key Enhancements:

1. Outlier Detection and Correction: Outliers in the original dataset have been systematically identified and corrected, providing more reliable financial figures.
2. Amendment Adjustments: In cases where SEC rules allow amendment filings to only include delta figures, full figures from the original submissions have been carried over for consistency, facilitating more straightforward analysis.
3. Missing Figure Estimation: Using calculation arcs from the US-GAAP taxonomy, missing financial figures have been computed where possible, ensuring greater completeness.
4. Data Structuring: Financial figures that previously appeared as separate rows have been consolidated into single rows with new columns, offering a cleaner structure.

Scope:

• Data Scope: The dataset is restricted to figures reported under US-GAAP standards, with the exception of EntityCommonStockSharesOutstanding and EntityPublicFloat.
• Currency and Units: The dataset exclusively includes figures reported in USD or shares, ensuring uniformity and comparability. It excludes ratios and non-financial metrics to maintain focus on financial data.
• Company Selection: The dataset is limited to companies with U.S. exchange tickers, providing a concentrated analysis of publicly traded firms within the United States.
• Submission Types: The dataset only incorporates data from 10-Q, 10-K, 10-Q/A, and 10-K/A filings, ensuring consistency in the type of financial reports analyzed.

Dataset Features:

• Refined Financial Data: Accurate and consistent figures by addressing reporting issues, corrections for outliers, and data consolidation.
• Enhanced Usability: By handling amendment submissions and leveraging GAAP taxonomies, the dataset offers a more analysis-friendly structure.
• Improved Completeness: Where original submissions had gaps in reporting, this dataset fills those gaps using calculated figures based on accounting principles.

The source code for data extraction is available here

The dataset included with this article contains three files describing and defining the sample and variables for VAT impact, and Excel file 1 consists of all raw and filtered data for the variables for the panel data sample. Excel file 2 depicts time-series and cross-sectional data for nonfinancial firms listed on the Saudi market for the second and third quarters of 2019 and the third and fourth quarters of 2020. Excel file 3 presents the raw material of variables used in measuring the company's profitability of the panel data sample

Introduction

This dataset contains 604 public company financial statement annually in IDX (Bursa Efek Indonesia), largest number that I can see in kaggle :D. Company that's not included in this dataset either do not report their financial statement or contains some irrelevant publishing date.

Usability

• EDA
• Classifier Stock
• Fundamental Analysis
• Financial Statement Analysis

Wanna Contribute?

Please leave a message on suggestions!

Appendix

Type:

Account:

(Formerly Public Accounts: Volume 2)

The Public Accounts of Ontario is a major accountability document which presents the financial statements of the province.

This dataset contains audited financial statements of consolidated organizations and Trusts under Administration.

Starting in 2018-19, Volume 2 is no longer part of the Public Accounts. Find the individual financial statements of government organizations (including hospitals, colleges and school boards), trusts under administration (such as the Workplace Safety and Insurance Board), businesses and other organizations on their websites. "https://www.ontario.ca/page/financial-statements-government-organizations-and-business-enterprises-2019-20">Access listing of organizations (2019-20).

The Financial Administration Act requires the preparation of the Public Accounts for each fiscal year.

The Public Accounts of Ontario are licenced under the Ontario.ca "https://www.ontario.ca/page/terms-use">terms of use (they are not subject to or licenced under the Open Government Licence).

See previous versions of the Public Accounts of Ontario. (Please note that the Public Accounts were only available in PDF format before 2015-16).

*[PDF]: Portable Document Format

Our comprehensive and advanced database is completed with all the information you need, with up to >1.5 million company financial records at your disposal. This allows you to easily perform company search on company profile and company directory, with 99% coverage in Malaysia.

Our database also contains company profiles on private limited or limited companies globally, including information such as shareholders and financial accounts can be accessed instantly.

Dataset Card for Financial Fraud Labeled Dataset

  Dataset Details

This dataset collects financial filings from various companies submitted to the U.S. Securities and Exchange Commission (SEC). The dataset consists of 85 companies involved in fraudulent cases and an equal number of companies not involved in fraudulent activities. The Fillings column includes information such as the company's MD&A, and financial statement over the years the company stated on the SEC… See the full description on the dataset page: https://huggingface.co/datasets/amitkedia/Financial-Fraud-Dataset.