Stochastic automatic differentiation: automatic differentiation for Monte-Carlo simulations

DOI10.1080/14697688.2018.1556398zbMath1420.91507OpenAlexW2729788879WikidataQ128553637 ScholiaQ128553637MaRDI QIDQ5234330

Christian Fries

Publication date: 26 September 2019

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697688.2018.1556398

zbMATH Keywords

conditional expectationautomatic differentiationindicator functionMonte Carlo simulationAmerican Monte Carloobject oriented implementationadjoint automatic differentiation

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Stochastic partial differential equations (aspects of stochastic analysis) (60H15)

Related Items (3)

Stochastic algorithmic differentiation of (expectations of) discontinuous functions (indicator functions) ⋮ Automatic adjoint differentiation for gradient descent and model calibration ⋮ Deep xVA Solver: A Neural Network–Based Counterparty Credit Risk Management Framework

Cites Work

• FAST MONTE CARLO GREEKS FOR FINANCIAL PRODUCTS WITH DISCONTINUOUS PAY-OFFS
• PERTURBATION STABLE CONDITIONAL ANALYTIC MONTE-CARLO PRICING SCHEME FOR AUTO-CALLABLE PRODUCTS
• Evaluating Derivatives
• Optimal Malliavin Weighting Function for the Computation of the Greeks
• AAD and least-square Monte Carlo: Fast Bermudan-style options and XVA Greeks
• Rapid and accurate development of prices and Greeks fornth to default credit swaps in the Li model
• Mathematical Finance

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