Malliavin Greeks without Malliavin calculus

By Nan Chen, Paul Glasserman. 2007

83 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/07a0679150f3772f8180fca2a7772e8ae64c7993

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Shakir Mohamed
2. Andriy Mnih
3. Ilya M. Sobol
4. Sergei S. Kucherenko
5. Mihaela Rosca
6. Michael Figurnov

In Finance

1. Shakir Mohamed
2. Andriy Mnih
3. Ilya M. Sobol
4. Sergei S. Kucherenko
5. Mihaela Rosca
6. Michael Figurnov

Citations in the corpus

• Construction and Comparison of High-Dimensional Sobol' Generators (2011, methodology): “These methods are based on the following ideas: differentiation of the paths and differentiation of the measures (see Glasserman, 2004; Chen and Glasserman, 2007).”
• Monte Carlo Gradient Estimation in Machine Learning (2019, methodology): “The generalised gradient methods based on weighting functions, called Malliavin weights, allows gradients to be computed in such settings, where the score function is replaced by a Skorohod integral (Chen and Glasserman, 2007).”