SEC Financial Filings with Derived Value Metrics

OpenFundex contains financial statement data extracted from SEC EDGAR filings, enriched with derived financial metrics and labeled with established quality scores. The dataset is designed for training machine learning models to assess company financial health and identify deep value opportunities. It was created by author ttchopper and was last updated in April 2026.

Use Cases

• Predict financial distress using labeled Altman Z'-Score derived from SEC filing data.
• Identify deep value investment opportunities by analyzing features labeled with Piotroski F-Score and Graham metrics.
• Train models to assess overall company financial health based on enriched financial statement metrics.

Strengths

• Data is enriched with derived financial metrics like Piotroski F-Score and Altman Z'-Score.
• Source data originates from authoritative SEC EDGAR filings.

Limitations

• Specific row count, column count, and temporal coverage are unknown.
• Potential geographic bias towards companies required to file with the U.S. SEC.

Provenance

Source

SEC EDGAR filings.

Collection Method

Extracted and enriched from financial statements.

Freshness

Last updated in April 2026.

Geography

Primarily United States (SEC jurisdiction).