Add to ORKGThis article is a follow up to Crépey, Frikha, and Louzi (2023), where we introduced a nested stochastic approximation algorithm and its multilevel acceleration for computing the value-at-risk and expected shortfall of a random financial loss. We establish central limit theorems for the renormalized errors associated with both algorithms and their averaged variations. Our findings are substantiated through numerical examples
We study the approximation of expectations E(f(X)) for solutions X of SDEs and functionals f : C([0,...
This paper examines the properties of various approximation methods for solving stochastic dynamic p...
44 pages, 9 figures.This paper studies multi-level stochastic approximation algorithms. Our aim is t...
This article is a follow up to Crépey, Frikha, and Louzi (2023), where we introduced a nested stocha...
We propose a multilevel stochastic approximation (MLSA) scheme for the computation of the Value-at-R...
We analyze three different methods that can approximate the expected shortfall of a financial portfo...
Abstract. This paper studies multi-level stochastic approximation algorithms. Our aim is to extend t...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
24 pages, 1 figureThis paper focuses on the study of an original combination of the Multilevel Monte...
This paper provides a general framework for the quantitative analysis of stochastic dynamic models. ...
We investigate the problem of computing a nested expectation of the form $\mathbb{P} {[\mathbb{E}[{X...
This paper proposes a unified method for precise estimates of the error bounds in asymptotic expansi...
Stochastic approximations is a rich branch of probability theory and has a wide range of application...
Stochastic approximations is a rich branch of probability theory and has a wide range of application...
We study the approximation of expectations E(f(X)) for solutions X of SDEs and functionals f : C([0,...
This paper examines the properties of various approximation methods for solving stochastic dynamic p...
44 pages, 9 figures.This paper studies multi-level stochastic approximation algorithms. Our aim is t...
This article is a follow up to Crépey, Frikha, and Louzi (2023), where we introduced a nested stocha...
We propose a multilevel stochastic approximation (MLSA) scheme for the computation of the Value-at-R...
We analyze three different methods that can approximate the expected shortfall of a financial portfo...
Abstract. This paper studies multi-level stochastic approximation algorithms. Our aim is to extend t...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
Stochastic approximation is a common paradigm for many stochastic recursions arising both as algorit...
24 pages, 1 figureThis paper focuses on the study of an original combination of the Multilevel Monte...
This paper provides a general framework for the quantitative analysis of stochastic dynamic models. ...
We investigate the problem of computing a nested expectation of the form $\mathbb{P} {[\mathbb{E}[{X...
This paper proposes a unified method for precise estimates of the error bounds in asymptotic expansi...
Stochastic approximations is a rich branch of probability theory and has a wide range of application...
Stochastic approximations is a rich branch of probability theory and has a wide range of application...
We study the approximation of expectations E(f(X)) for solutions X of SDEs and functionals f : C([0,...
This paper examines the properties of various approximation methods for solving stochastic dynamic p...
44 pages, 9 figures.This paper studies multi-level stochastic approximation algorithms. Our aim is t...