license: apache-2.0
task_categories:
- table-question-answering
- question-answering
language:
- en
tags:
- finance
- legal
size_categories:
- 100K<n<1M
SEC 10-X Filings Dataset
This dataset contains processed SEC 10-X (10-K, 10-Q) filings, focusing on Risk Factors and Management Discussion & Analysis (MD&A) sections from corporate financial reports from 1993-2023.
🔗 Original Dataset: [SEC-EDGAR-10X] contains stripped down versions of the original filings, details about which can be found here.
This dataset is a further cleaned tabulated version of the original stripped down version making it more suitable for training tasks.
Note: Documents with no match to risk factors or MD&A have been filtered out.
Dataset Description
Overview
This dataset is derived from SEC 10-X filings and provides structured access to two critical sections of corporate financial reports:
- Risk Factors (Item 1A)
- Management's Discussion and Analysis (Item 7)
The data has been processed to enable natural language processing and financial analysis tasks.
Processing Methodology
The dataset was created using a parsing pipeline that addresses several key considerations:
Risk Factors Extraction
- Multiple instances of risk factors may appear in a single filing
- The parser identifies all instances and selects the most comprehensive section
- When multiple valid sections are found, the longest section is retained to ensure completeness
MD&A Extraction
- Management Discussion & Analysis sections are identified and extracted
- Multiple MD&A sections within a filing are concatenated to preserve all relevant information
Data Organization
- Filings are grouped by CIK (Central Index Key) and filing date
- Multiple sections from the same filing are combined
- Empty or invalid entries are filtered out
Data Format
The dataset is stored in Parquet format with the following schema:
{
'CSI': 'string', # Central Index Key (CIK)
'FILE_DATE': 'string', # Filing date in YYYYMMDD format
'RISK_FACTOR': 'string', # Extracted Risk Factors section
'MD&A': 'string' # Extracted Management Discussion & Analysis section
}
Usage
Loading the Dataset
import datasets
dataset = datasets.load_dataset("theaayushbajaj/10-X-raw-v1", split="train")
Example Applications
- Risk analysis and classification
- Temporal analysis of corporate risk factors
- Business strategy analysis through MD&A
- Corporate disclosure analysis
- Financial sentiment analysis
Acknowledgments
- Securities and Exchange Commission (SEC) for providing access to the original filings
- University of Notre Dame for compiled versions