Here is the QuantLib license , the list of contributors , and the version history .

Just fork our repository on GitHub and start coding (instructions are here ). Please have a look at our developer intro and guidelines .

Open an issue on GitHub ; if you have a patch, open a pull request instead.

If you need to ask a question, subscribe to our mailing list and post it there. Before doing that, though, you might want to look at the FAQ and check if it was already answered.

Documentation is available in several formats from a number of sources. You can also read our installation instructions to get QuantLib working on your computer.

Head to our download page to get the latest official release, or check out the latest development version from our git repository. QuantLib is also available in other languages .

The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance. QuantLib is a free/open-source library for modeling, trading, and risk management in real-life.

QuantLib is written in C++ with a clean object model, and is then exported to different languages such as C#, Java, Python, R, and Ruby. An AAD-enabled version is also available. The reposit project facilitates deployment of object libraries to end user platforms and is used to generate QuantLibXL, an Excel addin for QuantLib, and QuantLibAddin, QuantLib addins for other platforms such as LibreOffice Calc. See the extensions page for details on bindings and ports to other languages.

Appreciated by quantitative analysts and developers, it is intended for academics and practitioners alike, eventually promoting a stronger interaction between them. QuantLib offers tools that are useful both for practical implementation and for advanced modeling, with features such as market conventions, yield curve models, solvers, PDEs, Monte Carlo (low-discrepancy included), exotic options, VAR, and so on.

Finance is an area where well-written open-source projects could make a tremendous difference:

any financial institution needs a solid, time-effective, operative implementation of cutting edge pricing models and hedging tools. However, to get there, one is currently forced to re-invent the wheel every time. Even standard decade-old models, such as Black-Scholes, still lack a public robust implementation. As a consequences many good quants are wasting their time writing C++ classes which have been already written thousands of times.

By designing and building these tools in the open, QuantLib will both encourage peer review of the tools themselves, and demonstrate how this ought to be done for scientific and commercial software. Dan Gezelter's talk at the first Open Source/Open Science conference discussed how the scientific tradition of peer review fits well with the philosophy of the Open Source movement. Open standards are the only fair way for science and technology to evolve.

The library could be exploited across different research and regulatory institutions, banks, software companies, and so on. Being a free/open-source project, quants contributing to the library would not need to start from scratch every time.

Students could master a library that is actually used in the real world and contribute to it in a meaningful way. This would potentially place them in a privileged position on the job market.

Researchers would have a framework at hand, which vastly reduces the amount of low-level work necessary to build models, so to be able to focus on more complex and interesting problems.

Financial firms could exploit QuantLib as base code and/or benchmark, while being able to engage in creating more innovative solutions that would make them more competitive on the market.

Regulatory institutions may have a tool for standard pricing and risk management practices.

The QuantLib license is a modified BSD license suitable for use in both free software and proprietary applications, imposing no constraints at all on the use of the library.

A few companies have committed significant resources to the development of this library; notably StatPro, a leading international risk-management provider, where the QuantLib project was born.