The Annals of Probability

Moderate deviation principles for stochastic differential equations with jumps

Amarjit Budhiraja, Paul Dupuis, and Arnab Ganguly

Full-text: Open access

Abstract

Moderate deviation principles for stochastic differential equations driven by a Poisson random measure (PRM) in finite and infinite dimensions are obtained. Proofs are based on a variational representation for expected values of positive functionals of a PRM.

Article information

Source
Ann. Probab., Volume 44, Number 3 (2016), 1723-1775.

Dates
Received: January 2014
Revised: January 2015
First available in Project Euclid: 16 May 2016

Permanent link to this document
https://projecteuclid.org/euclid.aop/1463410031

Digital Object Identifier
doi:10.1214/15-AOP1007

Mathematical Reviews number (MathSciNet)
MR3502593

Zentralblatt MATH identifier
1346.60026

Subjects
Primary: 60F10: Large deviations 60H15: Stochastic partial differential equations [See also 35R60] 60J75: Jump processes 60J25: Continuous-time Markov processes on general state spaces

Keywords
Moderate deviations large deviations Poisson random measures stochastic differential equations stochastic partial differential equations

Citation

Budhiraja, Amarjit; Dupuis, Paul; Ganguly, Arnab. Moderate deviation principles for stochastic differential equations with jumps. Ann. Probab. 44 (2016), no. 3, 1723--1775. doi:10.1214/15-AOP1007. https://projecteuclid.org/euclid.aop/1463410031


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