Advanced Quantitative Finance with Modern C++

From the elegance of the Black–Scholes equation to the complexity of multi-factor interest rate models and hybrid derivatives, this book is your comprehensive guide to quantitative finance, complete with 15+ advanced C++ projects using QuantLib and Boost.

You’ll move seamlessly from mathematical foundations to real-world implementation, building a professional-grade toolkit for pricing, risk analysis, and calibration. Inside, you will learn core option pricing methods, master single-and multi-factor interest rate models, and construct and calibrate trees and lattices for advanced derivatives. You will also explore cutting edge products: exotic multi-asset options, hybrid derivatives, credit instruments, and cross-currency swaps.

Packed with practical source code, step-by-step calibrations, and performance-tuned Boost integration, this book bridges the gap between academic finance and production-grade quant development. Whether you’re a quant developer, financial engineer, or an advanced student, you’ll gain the skills to design, implement, and deploy derivatives pricing models ready for the trading floor.

What You Will Learn

Understand the mathematics behind Black–Scholes, Vasicek, Hull–White, CIR, BDT, Black–Karasinski, and other core models.
Apply finite difference schemes, trinomial trees, and Monte Carlo simulations for derivative pricing.
Build and value swaps, swaptions, FRAs, bonds, callable/convertible debt, and multi-curve term structures.
Implement barrier, multi-asset, hybrid, and structured products in C++.
Model credit default swaps, cross-currency swaps, and total return structures.
Use QuantLib and Boost to create production-grade pricing engines and calibration tools.
Employ Gaussian models, market models, and global optimizers for fitting market data.
Integrate code into professional workflows, ensuring speed, accuracy, and maintainability.

Who This Book is for:

Quantitative developers, financial engineers, traders, analysts, and graduates students using C++, QuantLib, Boost, and robust tools to price, hedge, and manage risk for complex financial instruments—and for software engineers aiming to bridge theory and industry practice in quantitative finance.

Optional prerequisite: Mastering Quantitative Finance with Modern C++: Foundations, Derivatives, and Computational Methods, for readers who want to build a solid foundation before tackling the advanced models and projects in this book.