Stochastic Volterra Equations for Local Times of Spectrally Positive L\'evy Processes with Gaussian Components
Wei Xu

TL;DR
This paper studies the evolution of local times of spectrally positive Lévy processes with Gaussian components, using stochastic Volterra equations driven by Gaussian white noise and Poisson measures, establishing existence, uniqueness, and properties.
Contribution
It introduces a stochastic Volterra equation framework for local times of Lévy processes with Gaussian components, proving strong solutions and deriving new properties and representations.
Findings
Established strong existence and uniqueness of solutions.
Derived a comparison principle and stochastic flow for local times.
Provided an exponential-affine Laplace functional representation.
Abstract
Following our previous work [68], this paper continues to investigate the evolution dynamics of local times of spectrally positive L\'evy processes with Gaussian components in the spatial direction. We prove that conditioned on the finiteness of the first time at which the local time at zero exceeds a given value, local times at positive line are equal in law to the unique solution of a stochastic Volterra equation driven by a Gaussian white noise and two Poisson random measures with convolution kernel given in terms of the scale function. Also, we obtain several equivalent stochastic equations by using the potential theoretic techniques and prove the strong existence and uniqueness by using the generalized Yamada-Watanabe theorems. Armed with the stochastic Volterra representation, we then establish a comparison principle for the local times of spectrally positive L\'evy processes…
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Taxonomy
TopicsStochastic processes and financial applications · advanced mathematical theories · Mathematical Biology Tumor Growth
