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Invariant probability measures for path-dependent random diffusions

Jianhai Bao, Jinghai Shao, Chenggui Yuan Orcid Logo

Nonlinear Analysis, Volume: 228, Start page: 113201

Swansea University Author: Chenggui Yuan Orcid Logo

Abstract

In this work, we are concerned with path-dependent random diffusions. Under certain ergodic condition, we show that the path-dependent random diffusion under consideration has a unique invariant probability measure and converges exponentially to its equilibrium under the Wasserstein distance. Also,...

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Published in: Nonlinear Analysis
ISSN: 0362-546X
Published: Elsevier BV 2023
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa62231
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Abstract: In this work, we are concerned with path-dependent random diffusions. Under certain ergodic condition, we show that the path-dependent random diffusion under consideration has a unique invariant probability measure and converges exponentially to its equilibrium under the Wasserstein distance. Also, we demonstrate that the time discretization of the path-dependent random diffusion involved admits a unique (numerical) invariant probability measure and preserves the corresponding ergodic property when the step size is sufficiently small. Moreover, we provide an estimate on the exponential functional of the discrete observation for a Markov chain, which may be interesting by itself.
Keywords: Invariant probability measure; Path-dependent random diffusion; Ergodicity; Wasserstein distance; Euler–Maruyama scheme
College: Faculty of Science and Engineering
Start Page: 113201