Derivative formulae for stochastic differential equations driven by Poisson random measures

DOI10.1016/j.jmaa.2018.02.026zbMath1396.60070OpenAlexW2792681242MaRDI QIDQ1754605

Hua Zhang, Jiangang Ren

Publication date: 31 May 2018

Published in: Journal of Mathematical Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmaa.2018.02.026

zbMATH Keywords

gradient estimateLévy processesstochastic differential equationsDirichlet formPoisson functionalderivative formulae

Mathematics Subject Classification ID

Processes with independent increments; Lévy processes (60G51) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Random measures (60G57)

Related Items (1)

Strong Feller property for one-dimensional Lévy processes driven stochastic differential equations with Hölder continuous coefficients

Cites Work

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• Application of the lent particle method to Poisson-driven SDEs
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• Dirichlet forms and analysis on Wiener space
• Derivative formulas and gradient estimates for SDEs driven by \(\alpha\)-stable processes
• Derivative formulae for SDEs driven by multiplicative \(\alpha\)-stable-like processes
• Stochastic calculus of variations in mathematical finance.
• Energy image density property and the lent particle method for Poisson measures
• Dirichlet Forms Methods for Poisson Point Measures and Lévy Processes
• Ergodicity for Infinite Dimensional Systems
• Harnack Inequalities for Stochastic Partial Differential Equations

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