Rough SDEs and Robust Filtering for Jump-Diffusions

Fuente: arXiv
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Hauptverfasser: Allan, Andrew L., Pieper, Jost, Teichmann, Josef
Format: Preprint
Veröffentlicht: 2025
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author Allan, Andrew L.
Pieper, Jost
Teichmann, Josef
author_facet Allan, Andrew L.
Pieper, Jost
Teichmann, Josef
contents We investigate the existence of a robust, i.e., continuous, representation of the conditional distribution in a stochastic filtering model for multidimensional correlated jump-diffusions. Even in the absence of jumps, it is known that in general such a representation can only be continuous with respect to rough path topologies, leading us naturally to express the conditional dynamics as a rough stochastic differential equation with jumps. Via the analysis of such equations, including exponential moments, Skorokhod continuity, and randomisation of the rough path, we establish several novel robustness results for stochastic filters.
format Preprint
id arxiv_https___arxiv_org_abs_2507_05930
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Rough SDEs and Robust Filtering for Jump-Diffusions
Allan, Andrew L.
Pieper, Jost
Teichmann, Josef
Probability
60L20, 60G35
We investigate the existence of a robust, i.e., continuous, representation of the conditional distribution in a stochastic filtering model for multidimensional correlated jump-diffusions. Even in the absence of jumps, it is known that in general such a representation can only be continuous with respect to rough path topologies, leading us naturally to express the conditional dynamics as a rough stochastic differential equation with jumps. Via the analysis of such equations, including exponential moments, Skorokhod continuity, and randomisation of the rough path, we establish several novel robustness results for stochastic filters.
title Rough SDEs and Robust Filtering for Jump-Diffusions
topic Probability
60L20, 60G35
url https://arxiv.org/abs/2507.05930