Anonymous shelf assessment
Advanced Scripting for Derivatives
Shelf score 8.5 / 10
On Modern Computational Finance · Antoine Savine · Jesper Andreasen · John Wiley & Sons
Published 18 April 2026
This volume focuses on building professional derivative scripting systems with an emphasis on xVA applications.
Overview
Modern Computational Finance: Scripting for Derivatives and xVA serves as a comprehensive guide for quantitative finance professionals looking to enhance their scripting capabilities. The authors, Antoine Savine and Jesper Andreasen, delve into the intricacies of cash-flow representation and the implementation of advanced techniques such as American Monte Carlo methods. The text is designed for those with a solid foundation in C++ and derivatives, aiming to create maintainable and efficient scripting systems.
The book progresses from fundamental scripting concepts to complex control flows, highlighting the importance of modularity and performance in the context of evolving regulatory requirements. By integrating xVA considerations, it addresses the need for machine-auditable and batch-friendly payoff descriptions, making it relevant for contemporary risk management practices.
Readers are expected to gain competencies in designing scripting grammars, understanding Monte Carlo integration, and engaging in vendor evaluations with a technical perspective. This volume is particularly beneficial for teams modernising their risk assessment frameworks, as it pairs well with its predecessor, enhancing the overall learning experience.
By area & interest
Target Audience
This book is aimed at quantitative developers, risk managers, and analysts who are involved in the design and implementation of derivative scripting systems. It is particularly suited for professionals with a strong background in C++ and those familiar with the complexities of xVA.
Technical Depth
The text provides a rare focus on domain-specific language (DSL) architecture rather than solely on mathematical concepts, making it a unique resource in the field. It includes practical examples and a GitHub companion to facilitate implementation.
Complementary Volume
As the second volume in the series, it complements the first volume, which covers foundational aspects of computational finance. Together, they form a cohesive track for those looking to modernise their financial scripting capabilities.
Basis of this assessment
This assessment is based on the catalogue description and Google Books metadata, which provide insights into the book's content and target audience.
Strengths
The book's strengths lie in its practical focus on DSL architecture and its integration of real-world applications in risk systems. The authors' expertise and the inclusion of a GitHub companion enhance its utility for engineering-led teams.
Limitations
The content is tailored to a narrow audience, requiring significant C++ proficiency and systems thinking. It may not serve as a foundational text for those new to xVA economics or risk management.
Ideal reader
Ideal readers include quantitative developers and architects, xVA desk quants, and model-validation teams who are looking to deepen their understanding of scripting systems in finance.