Abstract The Multilevel Monte Carlo (MLMC) approach usually works well when estimating
the expected value of a quantity which is a Lipschitz function of intermediate quantities, but if …

We consider the problem of pricing basket options in a multivariate Black–Scholes or
Variance-Gamma model. From a numerical point of view, pricing such options corresponds …

We show how simple kinks and jumps of otherwise smooth integrands over R d can be dealt
with by a preliminary integration with respect to a single well chosen variable. It is assumed …

Preintegration is an extension of conditional Monte Carlo to quasi–Monte Carlo and
randomized quasi–Monte Carlo. Conditioning can reduce but not increase the variance in …

Many problems in derivative pricing can be formulated as high-dimensional integrals. Many
of them do not have closed-form solutions and have to be estimated by numerical …

Discontinuities and high dimensionality are common in the problems of pricing and hedging
of derivative securities. Both factors have a tremendous impact on the accuracy of the quasi …

Abstract Quasi-Monte Carlo (QMC) methods are efficient simulation tools for
multidimensional integrations in financial engineering. Discontinuous functions occur …

Abstract Quasi-Monte Carlo (QMC) methods have been gaining popularity in computational
finance as they are competitive alternatives to Monte Carlo methods that can accelerate …

We propose a new Monte Carlo-based estimator for digital options with assets modelled by
a stochastic differential equation (SDE). The new estimator is based on repeated path …

Conditional Monte Carlo or pre-integration is a powerful tool for reducing variance and
improving the regularity of integrands when using Monte Carlo and quasi-Monte Carlo …