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    Mini-symposium on automatic differentiation and its applications in the financial industry

    Geeraert, Sébastien and Lehalle, Charles-Albert and Pearlmutter, Barak A. and Pironneau, Olivier and Reghai, Adil (2017) Mini-symposium on automatic differentiation and its applications in the financial industry. Working Paper. arXiv.

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    Automatic differentiation is involved for long in applied mathematics as an alternative to finite difference to improve the accuracy of numerical computation of derivatives. Each time a numerical minimization is involved, automatic differentiation can be used. In between formal derivation and standard numerical schemes, this approach is based on software solutions applying mechanically the chain rule to obtain an exact value for the desired derivative. It has a cost in memory and cpu consumption. For participants of financial markets (banks, insurances, financial intermediaries, etc), computing derivatives is needed to obtain the sensitivity of its exposure to well-defined potential market moves. It is a way to understand variations of their balance sheets in specific cases. Since the 2008 crisis, regulation demand to compute this kind of exposure to many different case, to be sure market participants are aware and ready to face a wide spectrum of configurations. This paper shows how automatic differentiation provides a partial answer to this recent explosion of computation to perform. One part of the answer is a straightforward application of Adjoint Algorithmic Differentiation (AAD), but it is not enough. Since financial sensitivities involves specific functions and mix differentiation with Monte-Carlo simulations, dedicated tools and associated theoretical results are needed. We give here short introductions to typical cases arising when one use AAD on financial markets.

    Item Type: Monograph (Working Paper)
    Keywords: automatic differentiation; applications; financial industry;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 10228
    Identification Number: arXiv:1703.02311
    Depositing User: Barak Pearlmutter
    Date Deposited: 19 Nov 2018 15:52
    Publisher: arXiv
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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