Adjoint algorithmic differentiation tool support for typical numerical patterns in computational finance
نویسندگان
چکیده
منابع مشابه
Adjoint Algorithmic Differentiation Tool Support for Typical Numerical Patterns in Computational Finance
We demonstrate the flexibility and ease of use of C++ algorithmic differentiation (AD) tools based on overloading to numerical patterns (kernels) arising in computational finance. While adjoint methods and AD have been known in the finance literature for some time, there are few tools capable of handling and integrating with the C++ codes found in production. Adjoint methods are also known to b...
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ژورنال
عنوان ژورنال: Journal of Computational Finance
سال: 2018
ISSN: 1460-1559
DOI: 10.21314/jcf.2018.339