6 citations · 8 across the 10 of their papers we have counts for
6 papers · 1 filter
Hierarchical adaptive sparse grids and quasi Monte Carlo for option pricing under the rough Bergomi model
Christian Bayer, Chiheb Ben Hammouda, Raul Tempone
The rough Bergomi (rBergomi) model, introduced recently in [5], is a promising rough volatility model in quantitative finance. It is a parsimonious model depending on only three pa…
Multilevel Double Loop Monte Carlo and Stochastic Collocation Methods with Importance Sampling for Bayesian Optimal Experimental Design
Joakim Beck, Ben Mansour Dia, Luis F. R. Espath +1
An optimal experimental set-up maximizes the value of data for statistical inferences and predictions. The efficiency of strategies for finding optimal experimental set-ups is part…
Multilevel Monte Carlo Acceleration of Seismic Wave Propagation under Uncertainty
Marco Ballesio, Joakim Beck, Anamika Pandey +3
We interpret uncertainty in a model for seismic wave propagation by treating the model parameters as random variables, and apply the Multilevel Monte Carlo (MLMC) method to reduce…
Pricing American Options by Exercise Rate Optimization
Christian Bayer, Raúl Tempone, Sören Wolfers
We present a novel method for the numerical pricing of American options based on Monte Carlo simulation and the optimization of exercise strategies. Previous solutions to this prob…
Nesterov-aided Stochastic Gradient Methods using Laplace Approximation for Bayesian Design Optimization
Andre Gustavo Carlon, Ben Mansour Dia, Luis FR Espath +2
Finding the best setup for experiments is the primary concern for Optimal Experimental Design (OED). Here, we focus on the Bayesian experimental design problem of finding the setup…
Spatial Poisson processes for fatigue crack initiation
Ivo Babuska, Zaid Sawlan, Marco Scavino +2
In this work we propose a stochastic model for estimating the occurrence of crack initiations on the surface of metallic specimens in fatigue problems that can be applied to a gene…