Automatic backward differentiation for American Monte Carlo

Backward differentiation

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Christian Fries derives a modified backward automatic differentiation (also known as adjoint algorithmic differentiation for algorithms containing conditional expectation operators or indicator functions. Bermudan option and XVA valuation areprototypical applications. Featuring a clean-and-simple implementation, this method improves accuracy and performance. It also enables accurate ‘per-operator’ differentiation of the

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