Datasets:

idleengine
/

openfundex

license: cc-by-4.0
language:
  - en
pretty_name: OpenFundex
tags:
  - finance
  - value-investing
  - sec-filings
  - fundamental-analysis
  - tabular
task_categories:
  - tabular-classification
  - tabular-regression
size_categories:
  - 100K<n<1M
configs:
  - config_name: default
    default: true
    data_files:
      - split: train
        path: train_clean.parquet
      - split: validation
        path: validation_clean.parquet
      - split: test
        path: test_clean.parquet
  - config_name: full
    data_files:
      - split: train
        path: train.parquet
      - split: validation
        path: validation.parquet
      - split: test
        path: test.parquet
  - config_name: live
    data_files:
      - split: clean
        path: recent_clean.parquet
      - split: full
        path: recent.parquet

OpenFundex Dataset

A structured dataset of SEC financial filings for deep value analysis and financial distress prediction.

Dataset Description

License: CC-BY-4.0
Language: English

Summary

OpenFundex contains financial statement data extracted from SEC EDGAR filings, enriched with derived financial metrics and labeled with established quality scores (Piotroski F-Score, Altman Z'-Score, Graham metrics). Designed for training ML models to assess company financial health and identify deep value opportunities.

Key design decision: This dataset uses only fundamental data from SEC filings. No market prices or equity trading data are included, eliminating survivorship bias.

Supported Tasks

Tabular Classification: Predict financial distress, bankruptcy, value creation, fundamental improvement
Tabular Regression: Predict quality scores (f_score, z_prime_score, composite_quality_score), growth rates
Anomaly Detection: Identify companies in financial distress or with QA anomalies

Dataset Structure

Splits

Split	Records	Companies	Date Range
train	221,779	11,786	2008-12-31 to 2019-12-31
validation	45,109	7,207	2020-01-31 to 2021-12-31
test	47,334	7,208	2022-01-31 to 2023-12-31
recent	43,288	6,507	2024-01-31 to 2026-02-28

Total records: 357,510

Feature Groups

Group	Count
Identifiers	5
Context	4
Raw Features (SEC XBRL)	33
Derived Features	8
Engineered Features	23
QA Flags	4
Prediction Targets	21
Rank Targets	14

Scoring Models

Piotroski F-Score (0-9): Nine binary signals measuring profitability, leverage, and operating efficiency. Null when no prior quarter available for delta signals.
Altman Z'-Score (Float): Private-firm bankruptcy risk variant with zone classification (safe/grey/distress). Null for financial firms (SIC 6000-6999).
Beneish Coverage (0-8): Count of computable M-Score components. Full M-Score is computed transiently during enrichment but not retained.
Graham Metrics: Graham Number, NCAV/share, tangible book value/share, net working capital/share, defensive score (0-5).
Quality Signals: Cash conversion ratio, accrual ratio, free cash flow margin.
Composite Quality Score: Z-score normalized average of key quality signals within each quarter cross-section.

Target Columns

21 forward-looking prediction targets using same-quarter year-over-year comparisons:

1-Year Targets

Growth rates (6): BVPS, equity, earnings, revenue, OCF, FCF growth
Level/delta (2): Forward ROE, margin expansion
Binary (5): ROA improved, fundamentals improved (≥3 of 5 metrics), value created (equity grew AND ROE>0), survived (filed Q+4 AND no bankruptcy in window; NULL when CIK is in dropout-cause cohort with cause ∈ {form_25_delisting, unexplained_dark} and the PIT gate is met — see Considerations), filed for bankruptcy (petition within 365 days)

2-Year Targets

Growth rates (6): Same metrics as 1-year, over 2-year horizon
Binary (2): Survived (filed Q+8 AND no bankruptcy in window; NULL when CIK is in dropout-cause cohort with cause ∈ {form_25_delisting, unexplained_dark} and the PIT gate is met — see Considerations), filed for bankruptcy (petition within 730 days)

Survived and bankruptcy targets are mutually exclusive by construction. All targets are null when forward quarter data is unavailable. A third NULL state (CP-1 / v0.7.0) excludes Form-25 (M&A proxy) and unexplained-dark dropouts from the negative class to avoid mislabeling acquired companies as failed survivors.

Rank-Transformed Targets (14 columns)

Cross-sectional percentile ranks (0-1] for all Float64 targets, computed per quarter using rank("average") / count(). Raw growth targets are extremely skewed (mean ~3.1, median ~0.03) and produce negative information coefficients for regression models. Rank-transforming yields IC ~0.37.

Dataset Creation

Source Data

All data sourced from SEC EDGAR: Financial Statement Data Sets (FSDS) for fundamentals and Full-Text Search API (EFTS) for 8-K Item 1.03 bankruptcy filings. No market data providers. No third-party data. No equity pricing data.

Pipeline

Ingest: Download quarterly SEC FSDS ZIP files and bankruptcy events from EDGAR
Parse: Extract XBRL financial data, normalize 32 tags to standard fields
Enrich: Compute derived ratios (8), scoring models (5), bankruptcy flags, and QA flags
Label: Generate 21 forward-looking prediction targets (including bankruptcy)
Split: Temporal train/validation/test/recent splits with leakage validation
Evaluate: Quality checks, ML fitness, and publication readiness
Publish: Stage and upload to Hugging Face Hub

Considerations

Known Limitations

XBRL coverage varies: some companies report fewer standardized tags
F-Score delta components require prior quarter data (null for first appearance)
Z'-Score was designed for manufacturing firms; interpretation varies by sector
No market data: cannot compute price-based metrics (P/E, market cap, etc.)
bankruptcy_chapter is populated for bankrupt CIKs (values like "7", "11", "15", "9" extracted via 8-K Item 1.03 filing bodies); non-bankrupt rows are null. Edge cases not yet handled: chapter spelled out as a word ("chapter eleven") and USC-only citations with no "chapter" keyword both yield null.

Bias Considerations

Survivorship bias (Audit C1 / C1.1, 2026-05-05/06): the panel is built from SEC FSDS XBRL filings, so companies that stopped filing leave the panel silently. An audit of the 2009Q2–2026Q1 window classified 8,847 stopped-filing CIKs by cause: 54.4% Form-15 deregistration, 33.3% unexplained-dark, 8.7% bankruptcy, 3.6% Form-25 delisting (M&A proxy). LoPucki BRD intersect analysis (Audit C1.1) shows 21.4% of in-window Chapter 7/11 bankruptcies (83/388) are entirely absent from the panel, concentrated 2009–2011 during the XBRL ramp-up — a structural lower bound on missed bankruptcies.
Survival target NULL semantics (CP-1 / v0.7.0): target_survived_1y and target_survived_2y are set to NULL on rows where the CIK appears in the bundled dropout-cause cohort with cause ∈ {form_25_delisting, unexplained_dark} and the PIT gate is met (Form-25 evidence_date falls inside the label horizon, or unexplained_dark always-NULL). This avoids mislabeling acquired companies (Form-25 = M&A proxy) and unexplained dropouts as failed survivors. Bankruptcy and Form-15 CIKs remain in the negative class. The cohort artifact is shipped with the package at openfundex/cohorts/_data/dropout_causes.parquet and regenerable via ofx cohorts refresh dropout-causes.
Temporal integrity: Strict time-based splits prevent data leakage
Sector bias: Z'-Score thresholds may not be equally applicable across all sectors
Financial firms excluded from Z'-Score: Financial companies (SIC 6000-6999) have null Z'-Score values

License

This dataset is released under the CC-BY-4.0 license.

The underlying SEC data is in the public domain.

Citation

@dataset{openfundex,
  title={OpenFundex: SEC Financial Filings for Deep Value Analysis},
  author={Danielson, Luke},
  year={2026},
  url={https://github.com/danielukea/openfundex},
  license={CC-BY-4.0}
}

Changelog

v0.7.0 — 2026-05-14

target_survived_{1y,2y} NULL semantics widened (CP-1): rows where the CIK appears in the bundled dropout-cause cohort with cause ∈ {form_25_delisting, unexplained_dark} and the PIT gate is met are now NULL instead of False. This excludes M&A proxies and unknown-cause dropouts from the survival negative class to avoid mislabeling acquired companies. Bankruptcy and Form-15 CIKs remain negatives. Schema unchanged; this is a value-contract change. See Considerations § Survivorship bias.
New bundled package data: src/openfundex/cohorts/_data/dropout_causes.parquet (8,847 CIKs classified by precedence). Regenerable via ofx cohorts refresh dropout-causes.

v0.6.0 — 2026-04-17

bankruptcy_chapter populated: Chapter number ("7", "11", "15", "9") is now extracted from the 8-K Item 1.03 filing body for each bankrupt CIK and stored in the bankruptcy_chapter column. Non-bankrupt rows remain null. Extraction uses a guardword-gated Item 1.03 window search; known limitations (word-spelled chapters, USC-only citations) are documented above.

v0.5.0 — 2026-04-17

Loader contract: dataset card now declares explicit configs and data_files. load_dataset("ttchopper/openfundex") returns the QA-filtered historical splits (train/validation/test); unfiltered historical data is available via load_dataset(..., "full"); live 2024+ inference data via load_dataset(..., "live").
Previously the card omitted configs:, causing the Hub to glob all parquets and misassemble splits (paired _clean files were concatenated or surfaced as extra splits, and recent* was not declared at all).
Raw parquet access (hf://datasets/ttchopper/openfundex/train.parquet) is unaffected.