genpark-heston-stochastic-volatility-cir-process-skill
Heston two-factor stochastic volatility model with Cox-Ingersoll-Ross (CIR) variance and Feller condition checking
Details
- External ID
- 1392442160
- Source
- GITHUB
- Company
- —
- Product
- genpark-heston-stochastic-volatility-cir-process-skill
- Website domain
- github.com
- Launched
- Sept. 28, 2026
- Cohort
- —
- Upvotes
- 7
- Upvotes percentile
- 0.05976172175249808
- Tags
- agent-skills, cir-process, correlated-brownian, feller-condition, heston-model, mcp, option-pricing, python-standard-library, quantitative-finance, stochastic-volatility, volatility-surface
- Fetched at
- Sept. 30, 2026, 1:02 a.m.
- Updated at
- Sept. 30, 2026, 1:02 a.m.
Enrichment
- Theme
- revenue optimization and billing analytics
- Vertical
- Fintech
- Function
- Analytics & BI
- Audience
- Developer
- AI stance
- Not AI
- Project type
- Hobby / open-source project
- Normalized one-liner
- stochastic volatility model for quantitative finance
- Manually corrected
- False
Could you build this?
Yes Simulating a Heston stochastic volatility model using Euler-Maruyama discretization, CIR variance process, and checking the Feller condition (2*kappa*theta > sigma^2) is standard quantitative finance code easily synthesized by AI.
Competitors
Other products that read as similar to this one — 225 launches clear the similarity bar, closest 8 shown.
Attention rank: #182 of 226 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 334 days after the earliest competitor.
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Other launches for this product
- No other launches for this product.
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