Nelson-Siegel parametric zero-coupon yield curve modeling engine fitting spot rates, decay factor, level, slope, and curvature components.
genpark-yield-curve-nelson-siegel-interpolator-skill
Production-Grade Quantitative Finance & Risk Engineering Agent Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)
genpark-yield-curve-nelson-siegel-interpolator-skill delivers zero-dependency quantitative finance, option Greeks calculation, Monte Carlo stochastic simulations, and fixed-income analytics engineered strictly using Python 3.9+ standard library.
🌟 Key Architectural Capabilities - Zero External Dependencies: Operates exclusively via pure Python (math, random, json). Zero NumPy/SciPy/QuantLib build dependencies. - Enterprise Financial Invariants: Implements formal Black-Scholes-Merton analytic differentials, Geometric Brownian Motion stochastic walks, Historical & Parametric VaR/CVaR, Macaulay/Modified duration & convexity, and Nelson-Siegel yield curve parameterizations. - Native Anthropic MCP Protocol: Compliant with standard JSON-RPC 2.0 stdio MCP specifications for Claude Desktop, Cursor, and Windsurf.
🏗️ Architectural Topology & State Machine
🔌 One-Click MCP Integration (Claude Desktop / Cursor)
Add to your claudedesktopconfig.json or cursor.json:
This skill contains pre-configured smithery.yaml and pyproject.toml manifests. Install directly via pip:
Maintained with ❤️ by GenPark AI Engineering • Powering Autonomous Quantitative Agents 🌍
From the project README.
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