Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein
distance Page 1 Bernoulli 25(4A), 2019, 2620–2648 https://doi.org/10.3150/18-BEJ1065 Sharp …

This book is an extended written version of the Master 2 course “Probabilités
Numériques”(ie, Numerical Probability or Numerical Methods in Probability) which has been …

This work presents an empirical analysis of popular scenario generation methods for
stochastic optimization, including quasi-Monte Carlo, moment matching, and methods based …

The aim of this work is to advocate the use of multifractional Brownian motion (mBm) as a
relevant model in financial mathematics. mBm is an extension of fractional Brownian motion …

We study the theoretical properties of a variational Bayes method in the Gaussian Process
regression model. We consider the inducing variables method introduced by Titsias (2009b) …

Higher institutions are increasingly embracing the use of computer technologies in
advancing education. Despite evidence pointing to the positive impact of computer …

Vector Quantization is the name given to discretization methods based on nearest
neighbour search. It was developed in the 1950s, mostly in signal processing and …

We consider a stochastic volatility asset price model in which the volatility is the absolute
value of a continuous Gaussian process with arbitrary prescribed mean and covariance. By …

In this paper, the impact of liquidity on the underlying asset is taken into account when
pricing European options through a discounting factor which depends on two factors, ie …

We review in this article pure quantization methods for the pricing of multiple exercise
options. These quantization methods have the common advantage, that they allow a …