Mastering Advanced Quantitative Finance with Modern C++ - de la Rosa, Aaron
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Erscheint vorauss. 12. Januar 2026
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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…mehr

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Produktbeschreibung
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. 
Autorenporträt
Aaron De la Rosa is a Senior Quantitative Analyst and Data Scientist with a strong background in programming, finance, and quantitative analysis. He holds an MSc in Finance and has extensive experience as a Senior Data Scientist. Aaron is proficient in Python, R, C++, and Matlab, and specializes in portfolio optimization, machine learning, deep learning, and algorithmic trading. As a Quantitative Developer, he has expertise in market and credit risk, sentiment analysis, web scraping, natural language processing, and large language models. Aaron possesses comprehensive financial, quantitative, and modeling expertise, along with strong problem-solving abilities, excellent analytical skills, and broad financial experience.   He is a highly skilled, motivated, competent, and certified Quant with over eight years of experience in quantitative analysis and statistical modeling. Aaron is capable of providing accurate forecasts, optimizing investment portfolios, and developing projects using his knowledge of various programming languages.