Quantlib (financial engineering function library)

Source: Internet
Author: User
A free/open-source library for quantitative Finance

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.

To help create a community around quantlib, we have created a page quantlibuniversity.

Quantlib is written in C ++ with a clean object model, and is then exported to different versions such as Python, Ruby, and scheme. an initial Excel add-in is also available. there are ports to. net Framework in C # (http://www.quantlib.net "and http://www.capetools.net /). bindings to other versions ages (including Java), and porting to DDD, Matlab/Ave ave, S-PLUS/R, Mathematica, COM/CORBA/soap ubuntures, fpml, are under consideration. see the extensions page for details.

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 terminated ), exotic options, VAR, and so on.

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

 

  • Any financial institution needs a solid, time-impact tive, 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-schles, still lack a public robust implementation. as a consequences before 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 other cial 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 cocould be exploited into SS different research and regulatory institutions, banks, software companies, and so on. being a free/open-source project, quants contributing to the library wocould not need to start from scratch every time.
  • Students cocould master a library that is actually used in the real world and contrisponto it in a meaningful way. This wocould potentially place them in a privileged position on the job market.
  • Researchers wowould have a framework at hand, which vastly has CES The amount of low-level work necessary to build models, so to be able to focus on more complex and interesting problems.
  • Financial firms cocould exploit quantlib as base code and/or benchmark, while being able to engage in creating more innovative solutions that wocould 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 Italia, a leading risk-management consulting firm in Italy, where the quantlib project was born and the globewide network academic, A non-profit organization whose goal is to promote open source and Distance Education and Scholarship.

Help deciding the development road-map and start contributing to the Library: The project-Overview page gives a summary of the work in progress. Documentation is also available.

Feedback and questions concerning this site and project can be directed to the quantlib-Users Mailing List.

 

 

  • Newbieprojects
  • Long term projects
  • Short term projects
  • Quantlib people
  • Debugging tips

 

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