| --- |
| 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 |
| --- |
| |
| # 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, 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 | 38,171 | 6,358 | 2024-01-31 to 2025-11-30 | |
| |
| **Total records:** 352,393 |
| |
| ### Feature Groups |
| |
| | Group | Count | |
| |-------|-------| |
| | Identifiers | 5 | |
| | Context | 4 | |
| | Raw Features (SEC XBRL) | 33 | |
| | Derived Features | 8 | |
| | Engineered Features | 23 | |
| | QA Flags | 4 | |
| | Prediction Targets | 19 | |
| | 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 |
| |
| 19 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** (4): ROA improved, fundamentals improved (≥3 of 5 metrics), value created (equity grew AND ROE>0), survived |
| |
| ### 2-Year Targets |
| - **Growth rates** (6): Same metrics as 1-year, over 2-year horizon |
| - **Binary** (1): Survived 2 years |
| |
| All targets are null when forward quarter data is unavailable. |
| |
| ### 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 exclusively from SEC EDGAR Financial Statement Data Sets (FSDS), 2009-present. |
| No market data providers. No third-party data. No equity pricing data. |
| |
| ### Pipeline |
| |
| 1. **Ingest**: Download quarterly SEC FSDS ZIP files from EDGAR |
| 2. **Parse**: Extract XBRL financial data, normalize 32 tags to standard fields |
| 3. **Enrich**: Compute derived ratios (8), scoring models (5), and QA flags |
| 4. **Label**: Generate 19 forward-looking prediction targets |
| 5. **Split**: Temporal train/validation/test/recent splits with leakage validation |
| 6. **Evaluate**: Quality checks, ML fitness, and publication readiness |
| 7. **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.) |
| |
| ### Bias Considerations |
| |
| - **No survivorship bias**: Uses only SEC filing data, not equity market prices |
| - **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](https://creativecommons.org/licenses/by/4.0/). |
| |
| The underlying SEC data is in the public domain. |
| |
| ## Citation |
| |
| ```bibtex |
| @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} |
| } |
| ``` |
| |
