10 papers
Ergodic approximation for the invariant distribution: An abstract framework for law-dependent dynamics
Aurélien Alfonsi, Vlad Bally, Lucia Caramellino +1
This paper studies the approximation of invariant distributions for a broad class of law-dependent dynamics, including McKean-Vlasov stochastic differential equations and Boltzmann…
Weak solutions of Stochastic Volterra Equations in convex domains with general kernels
Eduardo Abi Jaber, Aurélien Alfonsi, Guillaume Szulda
We establish new weak existence results for -dimensional Stochastic Volterra Equations (SVEs) with continuous coefficients and possibly singular one-dimensional non-convolution…
Euler-type approximation for the invariant measure: An abstract framework
Aurélien Alfonsi, Vlad Bally, Arturo Kohatsu-Higa
We establish a general framework to study the rate of convergence of a Euler type approximation scheme with decreasing time steps to the invariant measure, for a general class of s…
Weak error approximation for rough and Gaussian mean-reverting stochastic volatility models
Aurélien Alfonsi, Ahmed Kebaier
For a class of stochastic models with Gaussian and rough mean-reverting volatility that embeds the genuine rough Stein-Stein model, we study the weak approximation rate when using…
How can the dual martingale help solving the primal optimal stopping problem?
Aurélien Alfonsi, Ahmed Kebaier, Jérôme Lelong
Motivated by recent results on the dual formulation of optimal stopping problems, we investigate in this short paper how the knowledge of an approximating dual martingale can impro…
A tree-based Polynomial Chaos expansion for surrogate modeling and sensitivity analysis of complex numerical models
Faten Ben Said, Aurélien Alfonsi, Anne Dutfoy +4
This paper introduces Tree-based Polynomial Chaos Expansion (Tree-PCE), a novel surrogate modeling technique designed to efficiently approximate complex numerical models exhibiting…