High-performance TensorFlow library for quantitative finance.
PyTorch for Quantitative Finance : Refine Derivatives Hedging and Pricing with Architecture Alightment in Operators
Python wrappers around QuantLib and Pandas to easily generate volatility surfaces
exotx provides a simple and user-friendly interface for pricing and analyzing financial derivatives using QuantLib's advanced numerical methods.
Have an LLM (LangGraph agent) control QuantLib, the cache, your databases and any plug-in tools. Includes evaluator framework and an Excel/LibreOffice API in https://github.com/FulgentMcGuffin/cqfi-xl and makes use of https://github.com/FulgentMcGuffin/mcp_data
Option pricing+Greeks, bond pricing/yield & day-counts for DuckDB (Python, QuantLib)
A Quarto Workflow for financial documents following modelling standards from Excel. Automated finance document generation with data CI. For Quants and Financial Engineers
C++20/Python option pricing across analytic, Monte Carlo, PDE, Heston, and exotics.
Jupyter Notebook Docker image for x86_64 platform
options pricer web app with black-scholes, binomial trees, and live market data
Numerical derivatives-pricing and model-validation core: Monte Carlo, finite-difference PDEs, Greeks, and SABR/Heston calibration, each challenged against closed forms and QuantLib, with an SR 26-2-style validation report.
A Python library that simplifies working with QuantLib by providing high-level abstractions for common quantitative finance tasks. The library handles market conventions, rate helpers, and calibration boilerplate so users can focus on pricing logic rather than QuantLib's low-level API.
Institutional-grade Fixed Income pricing engine for yield curve bootstrapping and Nelson-Siegel-Svensson (NSS) optimization.
Options pricing engine — Black-Scholes, Heston & Merton Jump-Diffusion models calibrated to real market data
Python pricing library built on QuantLib: curves, fixed income, derivatives, exotic options, stochastic simulation, and XVA.
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