A note on Euler approximations for stochastic differential equations involving the local time at point zero

Abstract We consider the Euler–Maruyama method (EM) and the tamed Euler–Maruyama method (TEM) for stochastic differential equations involving the local time at point zero. We provide the rate of strong convergence where the drift coefficient satisfies a one-sided Lipschitz condition and the diffusion coefficient is global Lipschitz.

Authors

Institutions

Publication Details

Journal
Random Operators and Stochastic Equations
Published
2025-03-28
DOI
https://doi.org/10.1515/rose-2025-2017
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A note on Euler approximations for stochastic differential equations involving the local time at point zero

Kamal Hiderah
Random Operators and Stochastic Equations
Stochastic processes and financial applications
article

A note on Euler approximations for stochastic differential equations involving the local time at point zero

Kamal Hiderah
article en

Abstract

Abstract We consider the Euler–Maruyama method (EM) and the tamed Euler–Maruyama method (TEM) for stochastic differential equations involving the local time at point zero. We provide the rate of strong convergence where the drift coefficient satisfies a one-sided Lipschitz condition and the diffusion coefficient is global Lipschitz.

Random Operators and Stochastic EquationsVol. 33(3)
University of Aden (YE)
Openalex Percentile: Top 92%
Stochastic processes and financial applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A note on Euler approximations for stochastic differential equations involving the local time at point zero — Kamal Hiderah · Random Operators and Stochastic Equations (2025) | TGRS Research Map | TGRS