nomas research
Unlock structured, searchable Public SEC Data
5 followers
Unlock structured, searchable Public SEC Data
5 followers
I built this platform because working with SEC filings — like Taxonomies, 13F, insider transactions, or fail-to-deliver data — is frustratingly painful. The data is fragmented, poorly structured. I sanitize the data and now it is ready to use for company research and training AI model.
With Business Account, you get access to full 13F report with "Search via Security" which includes full report of SHARE holding, CALL and PUT holding and ranking, more on nomas.fyi
📊 Just launched: Portfolio Management for Everyone!
Track multiple companies in custom portfolios with:
• Real-time financial data (13F, insider trading, FTD)
• Expandable data views for better organization
• PDF export with formatted reports
• Custom taxonomy tracking
Perfect for due diligence and investment research 📈
#FinTech #Investing #PortfolioManagement
Unlock the Power of Financial Ratios: Your Complete Guide to Company Performance!
Just launched the Financial Ratios + Company Rating!
🚀 Just launched: Real-time insider trading alerts with intelligent security filtering!
https://nomas.fyi/news
As a financial data engineer, I'm excited to share a major feature we've built at Nomas - live insider trading updates that automatically refresh every minute with smart security filtering.
## 🔥 What's New:
Live Updates
- Real-time insider trading data from SEC filings
- Automatic refresh without manual intervention
- Smart conflict resolution to prevent data race conditions
Intelligent Security Filtering
- Create personalized watchlists of companies you care about
- Filter insider trading data to show only your selected securities
- Instant updates when you modify your watchlist
## 🎯 Key Features:
✅ Live Updates: Data fetched from SEC in real-time
✅ Smart Filtering: Only see insider trading for your watchlist companies
✅ Conflict Prevention: No more race conditions between updates and user actions
✅ Professional UI: Clean, intuitive interface with real-time feedback
✅ Mobile Responsive: Works seamlessly across all devices
Cleaned SEC Data for AI Training
Excited to share our comprehensive financial dataset that's perfect for training AI models!
What we've built:
15,000+ companies with complete fundamentals
100M+ fundamental datapoints (114,679,026 to be exact!)
9.7M+ insider trading records (7M+ non-derivative + 2.6M+ derivative)
26.4M failure-to-deliver entries for market microstructure analysis
15,096 institutional holdings from Form 13F filings
Why this matters for AI:
Clean, structured data - no more messy SEC parsing
Comprehensive coverage - all major financial metrics
Real-time updates - fresh data for model training
Multiple data types - fundamentals, trading, institutional activity
Perfect for:
Quantitative trading models
Financial sentiment analysis
Market prediction algorithms
Risk assessment AI
Portfolio optimization systems
Ready to train your next financial AI model? Check out our platform
https://nomas.fyi
Major Update: XBRL Taxonomy Normalization
We've just implemented a comprehensive mapping system that transforms complex XBRL taxonomy names into human-readable financial terms.
What we accomplished:
• Mapped 11,000+ SEC XBRL taxonomies to standardized display names
• Enhanced user experience with clear, professional terminology
• Added metadata chips showing XBRL taxonomy, SEC labels, and descriptions
• Maintained data integrity while improving usability
Example transformation:
• Before: "EntityCommonStockSharesOutstanding"
• After: "Common Stock, Shares Outstanding"
Impact:
This makes financial data analysis more accessible to professionals who need clear, standardized terminology without losing the technical precision required for accurate data retrieval.
The system now displays:
🔹 XBRL taxonomy chips for technical reference
🔹 SEC label chips for regulatory context
🔹 Full descriptions for comprehensive understanding
Perfect for financial analysts, accountants, and data professionals who work with SEC filings daily.
more on https://nomas.fyi