Learn QUANTLIB with Real Code Examples

QuantLib offers a comprehensive suite of financial instruments, including bonds, options, swaps, and interest rate derivatives.

Supports term structures, stochastic processes, Monte Carlo simulations, and numerical methods.

Provides tools for pricing, risk metrics, and analytics for financial instruments.

Accessible via C++ natively, with Python (QuantLib-Python), R, and .NET bindings.

Widely used in banking, insurance, and asset management for pricing and risk analysis.

Instrument classes (Vanilla, Exotic options, Bonds, Swaps)

Pricing engines and model implementations

Market data handling (yield curves, volatilities)

Risk metrics (Greeks, duration, convexity)

Simulation and numerical methods for pricing

Instrument - financial product (option, bond, swap)

Pricing Engine - algorithm to compute price

Term Structure - representation of interest rates over time

Quote - market input data (price, yield, volatility)

Calendar - defines business days and holidays

C++ source and header files

Python bindings (if using Python)

Market data input files

Test scripts and notebooks

Documentation and example usage

Define instrument and its parameters

Choose appropriate pricing engine

Provide market data inputs

Compute price and risk metrics

Perform sensitivity or scenario analysis

Beginner: price vanilla European option

Intermediate: build yield curve and price swaps

Advanced: calibrate model to market data

Expert: Monte Carlo pricing of exotic options

Architect: integrate QuantLib into trading platform

QuantLib vs Finmath: open-source vs commercial focus

QuantLib vs proprietary risk engines: flexibility vs support

QuantLib vs PyQL: Python wrapper differences

QuantLib vs RQuantLib: R interface convenience

QuantLib vs MATLAB Financial Toolbox: performance vs ecosystem

2000 - QuantLib initial release by Luigi Ballabio

2005 - Python bindings introduced

2008 - Enhanced term structures and stochastic processes

2012 - Improved Monte Carlo and numerical solvers

2015 - Support for new exotic instruments

2018 - Continuous integration and cross-platform support

2020 - Expanded Python, R, and .NET bindings

2022 - Latest C++17 improvements and bug fixes

2024 - Modernization and optimization for large portfolios

2025 - Continued community contributions and Python API refinements

QuantLib - open-source quantitative finance library

Instrument - financial product

Pricing Engine - algorithm to compute price

Term Structure - interest rate curve over time

Quote - market data input (price, yield, vol)