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A free/open-source library for quantitative finance modeling, trading, and risk management.

QuantLib is a comprehensive, free/open-source software framework for quantitative finance. Written in C++, it offers a clean object model and is exported to languages including C#, Java, Python, and R. QuantLibXL and QuantLibAddin extend its functionality to Excel and LibreOffice Calc. Appreciated by quantitative analysts, developers, academics, and practitioners, QuantLib facilitates practical implementation and advanced modeling. It serves institutions, banks, software companies, and regulators, providing base code, benchmarks, and tools for pricing and risk management. The library is licensed under a modified BSD license, suitable for both free and proprietary applications, allowing unrestricted usage. QuantLib enables financial firms to develop innovative, competitive solutions and researchers to focus on complex problems with a ready-to-use framework.
QuantLib is a comprehensive, free/open-source software framework for quantitative finance.
Explore all tools that specialize in optimize investment portfolios. This domain focus ensures QuantLib delivers optimized results for this specific requirement.
Explore all tools that specialize in portfolio optimization. This domain focus ensures QuantLib delivers optimized results for this specific requirement.
Supports pricing of complex options such as Asian, Barrier, and Lookback options using Monte Carlo and PDE methods.
Includes models such as Hull-White, Black-Karasinski, and G2++ for interest rate derivatives pricing and hedging.
Offers tools for modeling credit risk, including credit default swaps (CDS) and collateralized debt obligations (CDOs).
Provides methods for calibrating volatility surfaces to market data, ensuring accurate pricing of volatility-dependent derivatives.
Enables Monte Carlo simulations for pricing complex financial instruments and assessing portfolio risk.
Supports AAD for efficient calculation of sensitivities (Greeks), crucial for risk management and hedging.
Download the QuantLib library from the official website or GitHub repository.
Install a C++ compiler (e.g., GCC, Visual Studio) and development environment.
Build the library using the provided build scripts or CMake.
Install language bindings for preferred languages like Python or R.
Explore the documentation, examples, and tutorials to understand core concepts.
Write code to integrate QuantLib into your existing financial applications.
Test and validate the integration with sample data and scenarios.
Contribute back to the community by submitting bug reports, feature requests, or code contributions.
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