Modern Computational Finance: Scripting for Derivatives and Xva by Savine, Antoine

Modern Computational Finance: Scripting for Derivatives and Xva (Hardcover) (ISBN-13: 9781119540786)

Vendor: Antoine Savine
Product type: Books
Format: Hardcover
$95.00
$95.00
$95.00
Subtotal: $95.00
Modern Computational Finance: Scripting for Derivatives and Xva by Savine, Antoine

Modern Computational Finance: Scripting for Derivatives and Xva

$95.00
Modern Computational Finance: Scripting for Derivatives and Xva by Savine, Antoine

Modern Computational Finance: Scripting for Derivatives and Xva

$95.00
Format: Hardcover
Description
Description
x

An incisive and essential guide to building a complete system for derivative scripting

In Volume 2 of Modern Computational Finance Scripting for Derivatives and xVA, quantitative finance experts and practitioners Drs. Antoine Savine and Jesper Andreasen deliver an indispensable and insightful roadmap to the interrogation, aggregation, and manipulation of cash-flows in a variety of ways. The book demonstrates how to facilitate portfolio-wide risk assessment and regulatory calculations (like xVA).

Complete with a professional scripting library written in modern C++, this stand-alone volume walks readers through the construction of a comprehensive risk and valuation tool. This essential book also offers:

  • Effective strategies for improving scripting libraries, from basic examples--like support for dates and vectors--to advanced improvements, including American Monte Carlo techniques
  • Exploration of the concepts of fuzzy logic and risk sensitivities, including support for smoothing and condition domains
  • Discussion of the application of scripting to xVA, complete with a full treatment of branching

Perfect for quantitative analysts, risk professionals, system developers, derivatives traders, and financial analysts, Modern Computational Finance Scripting for Derivatives and xVA Volume 2 is also a must-read resource for students and teachers in master's and PhD finance programs.



Author: Antoine Savine, Jesper Andreasen
ISBN-10: 111954078X
ISBN-13: 9781119540786
Publisher: Wiley
Language: English
Published: 11/02/2021
Pages: 288
Format: Hardcover
Weight: 1.30lbs
Size: 9.40h x 6.40w x 0.90d
By Antoine Savine
By Antoine Savine
x

ANTOINE SAVINE is a mathematician and derivatives practitioner with 25 years of leadership experience with global investment banks. He wrote the book on automatic adjoint differentiation (AAD) and co-developed Differential Machine Learning. He was also influential in volatility modeling and many areas of numerical and computational finance. Antoine works with Superfly Analytics at Danske Bank, winner of the 2019 Excellence in Risk Management and Modelling RiskMinds award. He holds a PhD in Mathematical Finance from Copenhagen University, where he teaches quantitative and computational finance.

Jesper Andreasen heads the Quantitative Research department at Saxo Bank. Over a 25 year long career he has held senior roles in quant departments of Bank of America, Nordea and General Re Financial Products, and he founded and headed the Superfly Analytics department at Danske Bank. Jesper co-received Risk magazine's 2001 and 2012 Quant of the year awards and their In-House Risk System of the year award in 2015. He is an honorary professor of Mathematical Finance at Copenhagen University and completed his PhD in the same subject at Aarhus University in 1997.

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