Weak error for nested Multilevel Monte Carlo - Archive ouverte HAL
Article Dans Une Revue Methodology and Computing in Applied Probability Année : 2020

Weak error for nested Multilevel Monte Carlo

Résumé

This article discusses MLMC estimators with and without weights, applied to nested expectations of the form E [f (E [F (Y, Z)|Y ])]. More precisely, we are interested on the assumptions needed to comply with the MLMC framework, depending on whether the payoff function f is smooth or not. A new result to our knowledge is given when f is not smooth in the development of the weak error at an order higher than 1, which is needed for a successful use of MLMC estimators with weights.
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Dates et versions

hal-01817386 , version 1 (17-06-2018)

Identifiants

Citer

Daphné Giorgi, Vincent Lemaire, Gilles Pagès. Weak error for nested Multilevel Monte Carlo. Methodology and Computing in Applied Probability, 2020, 22 (3), pp.1325-1348. ⟨10.1007/s11009-019-09751-3⟩. ⟨hal-01817386⟩
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