Wasserstein distance estimates for jump-diffusion processes
We derive Wasserstein distance bounds between the probability distributions of a stochastic integral (Itô) process with jumps (Xt)t∈[0,T] and a jump-diffusion process (Xt∗)t∈[0,T]. Our bounds are expressed using the stochastic characteristics of (Xt)t∈[0,T] and the jump-diffusion coefficients of (Xt...
Saved in:
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/180130 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-180130 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1801302024-09-18T05:15:32Z Wasserstein distance estimates for jump-diffusion processes Breton, Jean-Christophe Privault, Nicolas School of Physical and Mathematical Sciences Mathematical Sciences Wasserstein distance Stochastic integrals We derive Wasserstein distance bounds between the probability distributions of a stochastic integral (Itô) process with jumps (Xt)t∈[0,T] and a jump-diffusion process (Xt∗)t∈[0,T]. Our bounds are expressed using the stochastic characteristics of (Xt)t∈[0,T] and the jump-diffusion coefficients of (Xt∗)t∈[0,T] evaluated in Xt, and apply in particular to the case of different jump characteristics. Our approach uses stochastic calculus arguments and Lp integrability results for the flow of stochastic differential equations with jumps, without relying on the Stein equation. Ministry of Education (MOE) The first author conducted this work within the France 2030 framework program, the Centre Henri Lebesgue ANR-11-LABX-0020-01. The second author is supported by the Ministry of Education, Singapore, under its Tier 2 Grant MOE-T2EP20120-0005. 2024-09-18T05:15:32Z 2024-09-18T05:15:32Z 2024 Journal Article Breton, J. & Privault, N. (2024). Wasserstein distance estimates for jump-diffusion processes. Stochastic Processes and Their Applications, 172, 104334-. https://dx.doi.org/10.1016/j.spa.2024.104334 0304-4149 https://hdl.handle.net/10356/180130 10.1016/j.spa.2024.104334 2-s2.0-85186659980 172 104334 en MOE-T2EP20120-0005 Stochastic Processes and their Applications © 2024 Elsevier B.V. All rights reserved. |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Mathematical Sciences Wasserstein distance Stochastic integrals |
spellingShingle |
Mathematical Sciences Wasserstein distance Stochastic integrals Breton, Jean-Christophe Privault, Nicolas Wasserstein distance estimates for jump-diffusion processes |
description |
We derive Wasserstein distance bounds between the probability distributions of a stochastic integral (Itô) process with jumps (Xt)t∈[0,T] and a jump-diffusion process (Xt∗)t∈[0,T]. Our bounds are expressed using the stochastic characteristics of (Xt)t∈[0,T] and the jump-diffusion coefficients of (Xt∗)t∈[0,T] evaluated in Xt, and apply in particular to the case of different jump characteristics. Our approach uses stochastic calculus arguments and Lp integrability results for the flow of stochastic differential equations with jumps, without relying on the Stein equation. |
author2 |
School of Physical and Mathematical Sciences |
author_facet |
School of Physical and Mathematical Sciences Breton, Jean-Christophe Privault, Nicolas |
format |
Article |
author |
Breton, Jean-Christophe Privault, Nicolas |
author_sort |
Breton, Jean-Christophe |
title |
Wasserstein distance estimates for jump-diffusion processes |
title_short |
Wasserstein distance estimates for jump-diffusion processes |
title_full |
Wasserstein distance estimates for jump-diffusion processes |
title_fullStr |
Wasserstein distance estimates for jump-diffusion processes |
title_full_unstemmed |
Wasserstein distance estimates for jump-diffusion processes |
title_sort |
wasserstein distance estimates for jump-diffusion processes |
publishDate |
2024 |
url |
https://hdl.handle.net/10356/180130 |
_version_ |
1814047389298720768 |