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Mastering quantitative finance with ...

De la Rosa, Aaron.

Mastering quantitative finance with modern C++foundations, derivatives, and computational methods /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mastering quantitative finance with modern C++by Aaron De la Rosa.
Reminder of title:	foundations, derivatives, and computational methods /
Author:	De la Rosa, Aaron.
Published:	Berkeley, CA :Apress :2025.
Description:	xxxviii, 877 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	C++ (Computer program language)
Online resource:	https://doi.org/10.1007/979-8-8688-1793-9
ISBN:	9798868817939$q(electronic bk.)

Mastering quantitative finance with modern C++foundations, derivatives, and computational methods /
De la Rosa, Aaron.

Mastering quantitative finance with modern C++foundations, derivatives, and computational methods /[electronic resource] :by Aaron De la Rosa. - Berkeley, CA :Apress :2025. - xxxviii, 877 p. :ill., digital ;24 cm.

1. Introduction to Modern C++23 -- 2. Components of an Object-Oriented C++ Program -- 3. Option Payoff Hierarchies in C++ -- 4. Generic Programming and Template Classes in C++ -- 5. Introduction to the Standard Template Library (STL) in C++23 -- 6. Function Objects in C++ -- 7. Matrix Classes for Quantitative Finance -- 8. Numerical Linear Algebra in C++ -- 9. Black Scholes and Pricing Fundamentals -- 10. Calculating the \Greeks -- 11. European Options with Monte Carlo Simulation -- 12. Binomial and Trinomial Trees -- 13. Finite Difference Methods -- 14. Asian/Path-Dependent Options with Monte Carlo -- 15. Exotic Options -- 16. Implied Volatility -- 17. Stochastic Volatility -- 18. Geometric Brownian Motion (GBM) and Jump-Diffusion Models.

Learn to build robust, scalable financial models to position yourself as an expert in computational finance. At a time when the financial industry demands an increasingly complex and accurate mode, this book ensures you stay ahead of the curve by leveraging the latest advancements in programming to develop faster, more reliable, and maintainable financial software. To begin, you'll explore key features of C++23, object-oriented programming, and template-based design patterns critical for building reusable financial components. From there, dive into a range of numerical methods, including Monte Carlo simulations, binomial and trinomial trees, and finite difference schemes. Special attention is given to practical implementation details. Every chapter is designed to guide you step by step in transforming mathematical models into efficient, production-level C++ code. You will also learn to handle exotic derivatives, stochastic volatility, and jump-diffusion models, bridging the gap between theory and practice. In the end, you'll be equipped with the technical foundation and practical tools needed to design, implement, and analyze complex financial products. You will also be well-prepared to tackle the advanced interest rate and credit derivatives covered in further depth in De La Rosa's Advanced Quantitative Finance with Modern C++. What You: Master modern C++23 syntax and features, including object-oriented and generic programming. Design flexible option payoff hierarchies for code reuse. Apply advanced numerical techniques such as Monte Carlo, binomial/trinomial trees, and finite difference methods. Calculate and interpret option sensitivities (Greeks). Model and price exotic options, including stochastic volatility and jump-diffusion models. Integrate mathematical finance concepts into production-quality C++ code.

ISBN: 9798868817939$q(electronic bk.)

Standard No.: 10.1007/979-8-8688-1793-9doiSubjects--Topical Terms:

181958
C++ (Computer program language)

LC Class. No.: QA76.73.C153

Dewey Class. No.: 005.133

Mastering quantitative finance with modern C++foundations, derivatives, and computational methods /
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505 0 $a 1. Introduction to Modern C++23 -- 2. Components of an Object-Oriented C++ Program -- 3. Option Payoff Hierarchies in C++ -- 4. Generic Programming and Template Classes in C++ -- 5. Introduction to the Standard Template Library (STL) in C++23 -- 6. Function Objects in C++ -- 7. Matrix Classes for Quantitative Finance -- 8. Numerical Linear Algebra in C++ -- 9. Black Scholes and Pricing Fundamentals -- 10. Calculating the \Greeks -- 11. European Options with Monte Carlo Simulation -- 12. Binomial and Trinomial Trees -- 13. Finite Difference Methods -- 14. Asian/Path-Dependent Options with Monte Carlo -- 15. Exotic Options -- 16. Implied Volatility -- 17. Stochastic Volatility -- 18. Geometric Brownian Motion (GBM) and Jump-Diffusion Models.
520 $a Learn to build robust, scalable financial models to position yourself as an expert in computational finance. At a time when the financial industry demands an increasingly complex and accurate mode, this book ensures you stay ahead of the curve by leveraging the latest advancements in programming to develop faster, more reliable, and maintainable financial software. To begin, you'll explore key features of C++23, object-oriented programming, and template-based design patterns critical for building reusable financial components. From there, dive into a range of numerical methods, including Monte Carlo simulations, binomial and trinomial trees, and finite difference schemes. Special attention is given to practical implementation details. Every chapter is designed to guide you step by step in transforming mathematical models into efficient, production-level C++ code. You will also learn to handle exotic derivatives, stochastic volatility, and jump-diffusion models, bridging the gap between theory and practice. In the end, you'll be equipped with the technical foundation and practical tools needed to design, implement, and analyze complex financial products. You will also be well-prepared to tackle the advanced interest rate and credit derivatives covered in further depth in De La Rosa's Advanced Quantitative Finance with Modern C++. What You: Master modern C++23 syntax and features, including object-oriented and generic programming. Design flexible option payoff hierarchies for code reuse. Apply advanced numerical techniques such as Monte Carlo, binomial/trinomial trees, and finite difference methods. Calculate and interpret option sensitivities (Greeks). Model and price exotic options, including stochastic volatility and jump-diffusion models. Integrate mathematical finance concepts into production-quality C++ code.
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