---
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}
}
```