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.
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
Jupyter Notebook Docker image for x86_64 platform
options pricer web app with black-scholes, binomial trees, and live market data
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.
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.
Python fund risk analytics for AIFM / ManCo workflows, covering leverage, VaR, stress testing, derivatives and liquidity methodology.
QuantLib IRS curve bootstrapping for EM rates: PLN, HUF, CZK, ZAR. Discount factors, zero rates, forward rates from market par swap rates.
Institutional-grade Fixed Income pricing engine for yield curve bootstrapping and Nelson-Siegel-Svensson (NSS) optimization.
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