US Publicly Traded Companies probabilities of default with public data
Details
- External ID
- 45921439
- Source
- HN
- Company
- —
- Product
- US Publicly Traded Companies probabilities of default with public data
- Website domain
- quantra.io
- Launched
- Nov. 13, 2025
- Cohort
- —
- Upvotes
- 7
- Upvotes percentile
- 0.37882096069869
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:25 p.m.
- Updated at
- Sept. 7, 2026, 9:25 p.m.
Enrichment
- Theme
- algorithmic trading bots and platforms
- Vertical
- Fintech
- Function
- Analytics & BI
- Audience
- B2B
- AI stance
- Not AI
- Project type
- Commercial product
- Normalized one-liner
- default probability predictions for public companies
- Manually corrected
- False
Could you build this?
Partial The dashboard UI and charts are straightforward web development, but calculating Merton structural default probabilities requires financial data pipelines (SEC EDGAR, market cap/equity volatility) and solving non-linear option pricing models.
What it would actually take: The system requires a Python backend with automated scrapers/parsers for SEC 10-K/10-Q filings and market equity price/volatility feeds. The hard component is implementing numerical solvers for the Merton model equations to estimate asset value and asset volatility from equity observables. Building this reliably requires quantitative finance domain expertise and robust financial data ingestion pipelines.
Discussion
No comments on this launch.
Competitors
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Attention rank: #106 of 191 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 15 days after the earliest competitor.
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Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a analytics & bi tool for Legal yet.