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genpark-monte-carlo-geometric-brownian-motion-skill

Geometric Brownian Motion (GBM) Monte Carlo stochastic path simulation engine with normal Box-Muller variates and tail percentile bounds.

Details

External ID
1391738409
Source
GITHUB
Company
—
Product
genpark-monte-carlo-geometric-brownian-motion-skill
Website domain
github.com
Launched
Sept. 28, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.05976172175249808
Tags
agentic-ai, asset-pricing, financial-engineering, geometric-brownian-motion, mcp, mcp-server, model-context-protocol, monte-carlo, quantitative-finance, stochastic-simulation, zero-dependency
Fetched at
Sept. 30, 2026, 1:02 a.m.
Updated at
Sept. 30, 2026, 1:02 a.m.

Enrichment

Theme
3D graphics and physics simulation tools
Vertical
Fintech
Function
Analytics & BI
Audience
Developer
AI stance
Not AI
Project type
Hobby / open-source project
Normalized one-liner
monte carlo stochastic path simulator for financial modeling
Manually corrected
False

Could you build this?

Yes Geometric Brownian Motion simulations using Box-Muller transforms and NumPy/standard libraries are foundational quant finance scripts that an AI assistant can generate in minutes.

Competitors

Other products that read as similar to this one — 455 launches clear the similarity bar, closest 8 shown.

Attention rank: #317 of 456 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 328 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a analytics & bi tool for Legal yet.