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 derivates. 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.

You Will:

• 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.

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.