QuantLib-Risks-Cpp
Risk calculator
Integration of XAD automatic differentiation with QuantLib risk analysis in C++
Fast risks with QuantLib in C++
15 stars
2 watching
11 forks
Language: C++
last commit: about 2 months ago
Linked from 1 awesome list
algorithmic-differentiationquantitative-financerisk-analysis
Related projects:
Repository | Description | Stars |
---|---|---|
auto-differentiation/quantlib-risks-py | Provides fast risk calculations using the QuantLib Python library with automatic differentiation | 10 |
auto-differentiation/xad | A high-performance tool for computing derivatives of complex functions used in various scientific and engineering applications. | 258 |
auto-differentiation/xad-py | Provides automatic differentiation capabilities for numerical computations in Python | 10 |
eddelbuettel/rquantlib | Provides R interface to QuantLib library for quantitative finance analysis | 120 |
autodiff/autodiff | A C++ library that enables automatic computation of derivatives in an efficient and intuitive way | 1,660 |
quantsbin/quantsbin | Provides tools for pricing and analyzing financial derivatives in Python | 500 |
choucrifahed/quantscale | A Scala library built on top of QuantLib's C++ implementation, providing a quantitative finance solution with concurrent capabilities using Akka and Scala STM. | 46 |
d-bahr/crcpp | An efficient C++ implementation of a portable and lightweight CRC algorithm | 337 |
qgrad/qgrad | Integrates automatic differentiation tools with quantum software packages. | 43 |
enthought/pyql | A Cython-based wrapper library for QuantLib financial calculations | 1,007 |
bluescarni/mppp | A high-performance C++ library for arbitrary-precision arithmetic and special functions | 306 |
quantopian/empyrical | A Python library providing common financial risk and performance metrics. | 1,310 |
nathanawmk/top-10-cicd-security-risks | An analysis of common security risks in Continuous Integration/Continuous Deployment systems and processes. | 3 |
alexshtf/autodiff | A .NET library that automates the process of computing derivatives of mathematical functions. | 92 |
lechgrzelak/quantfinancebook | Provides Python implementations of mathematical modeling and computation in finance exercises from a popular book | 496 |