Remarks on stochastic automatic adjoint differentiation and financial models calibration

Dmitri Goloubentsev and Evgeny Lakshtanov

Papers from arXiv.org

Abstract: In this work, we discuss the Automatic Adjoint Differentiation (AAD) for functions of the form $G=\frac{1}{2}\sum_1^m (Ey_i-C_i)^2$, which often appear in the calibration of stochastic models. { We demonstrate that it allows a perfect SIMD\footnote{Single Input Multiple Data} parallelization and provide its relative computational cost. In addition we demonstrate that this theoretical result is in concordance with numeric experiments.}

Date: 2019-01, Revised 2019-12
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1901.04200

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