Titlebook: Algorithmic Differentiation in Finance Explained; Marc Henrard Book 2017 The Editor(s) (if applicable) and The Author(s) 2017 Algorithmic

hemophilia

Gang Wang,Arridhana Ciptadi,Ali AhmadzadehIt seems there is no easy starting point for reviewing Algorithmic Differentiation in finance. Each function, especially in the simpler one, seems to be an exception with a particular trick more than a general direct application of the methodology.

摘要

https://doi.org/10.1007/978-3-030-87839-9The title of this chapter may appear a little bit cryptic. The main advertised goal of Algorithmic Differentiation (AD) is to compute in an efficient way the derivatives of functions with respect to their inputs. Each part of this chapter’s title may appear in contraction with that general goal.

無目標

The Principles of Algorithmic Differentiation,The starting point of everything is obviously the definition of ., the notion we are planning to compute through Algorithmic Differentiation (AD).

闡明

Application to Finance,It seems there is no easy starting point for reviewing Algorithmic Differentiation in finance. Each function, especially in the simpler one, seems to be an exception with a particular trick more than a general direct application of the methodology.

meditation

NAG

ATRIA

Automatic Algorithmic Differentiation,riting code that performs the Algorithmic Differentiation automatically. The developments required are relatively heavy at the start, but from there on, there should be only a minimal development cost.

FLUSH

Comprise

sitivities of a portfolio with machine precision.. .Written by a leading practitioner who works and programmes AD, it offers a practical analysis of all the major applications of AD in the derivatives se978-3-319-53978-2978-3-319-53979-9

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