English

Stochastic analysis for vector-valued generalized grey Brownian motion

Probability 2021-11-18 v1 Functional Analysis

Abstract

In this article, we show that the standard vector-valued generalization of a generalized grey Brownian motion (ggBm) has independent components if and only if it is a fractional Brownian motion. In order to extend ggBm with independent components, we introduce a vector-valued generalized grey Brownian motion (vggBm). The characteristic function of the corresponding measure is introduced as the product of the characteristic functions of the one-dimensional case. We show that for this measure, the Appell system and a calculus of generalized functions or distributions are accessible. We characterize these distributions with suitable transformations and give a d-dimensional Donsker's delta function as an example for such distributions. From there, we show the existence of local times and self-intersection local times of vggBm as distributions under some constraints, and compute their corresponding generalized expectations. At the end, we solve a system of linear SDEs driven by a vggBm noise in d dimensions.

Keywords

Cite

@article{arxiv.2111.09229,
  title  = {Stochastic analysis for vector-valued generalized grey Brownian motion},
  author = {Wolfgang Bock and Martin Grothaus and Karlo Orge},
  journal= {arXiv preprint arXiv:2111.09229},
  year   = {2021}
}
R2 v1 2026-06-24T07:42:23.438Z