Auf Lager:
6
Buch (Softcover): Fachbuch
Mastering Quantitative Finance with Modern C++
Foundations, Derivatives, and Computational Methods
Produkt bewerten
Verlag:
Springer EN Unsere-Artikel-Nr.: N3WPYGY
EAN: 9798868817922
Auf Lager:
6
Zustellung: Mi, 01.07.2026
Versand: Kostenlos
-10.4 %
CHF 96.–
CHF 86.–
Beschreibung
Learn to build robust, scalable financial models to position yourself as an expert in computational finance. At a time when the financial industry demands 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. Begin with a solid introduction to modern C and its relevance to engineering. From there, you will discover the heart of financial modelling, starting with Black-Scholes fundamentals and progressing through critical topics such as Monte Carlo simulations, binomial and trinomial trees, finite difference methods, and option Greeks. Practical implementation of Asian and exotic options will ensure you grasp real-world applications of these models. Then, you will prepare to tackle complex market dynamics with advanced topics, including stochastic volatility, implied volatility, and jump-diffusion models. Additional topics include cutting-edge interest rate modelling techniques, such as the Hull-White tree, Vasicek, and Cox-Ingersoll-Ross models, as well as Bermudan and exotic interest rate derivatives—essential for fixed-income professionals. Real-world examples, combined with hands-on coding exercises, help illustrate the theory behind solving challenging problems in finance. Beyond theoretical discussions, Mastering Advanced Quantitative Finance with Modern C. emphasizes numerical techniques, such as numerical linear algebra and random number generation, empowering readers to implement efficient computational solutions.
Spezifikationen
Sprache
- Englisch
Autor
- Aaron De la Rosa
Zielgruppe
- Professional/practitioner
Erscheinungsjahr
- 2026
Format
- Buch (Softcover)
Anzahl Seiten
- 877