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math.PR2026

Weak solutions to distribution-dependent stochastic Volterra equations

Martin Bergerhausen, David J. Prömel

We prove the existence of weak solutions for distribution-dependent stochastic Volterra equations under linear growth and continuity conditions on the coefficients and mild regular…

math.PR2026

Stochastic differential equations driven by fractional Brownian motion: dependence on the Hurst parameter

Anna P. Kwossek, Andreas Neuenkirch, David J. Prömel

Stochastic models with fractional Brownian motion as source of randomness have become popular since the early 2000s. Fractional Brownian motion (fBm) is a Gaussian process, whose c…

math.PR2025

Mean-field stochastic Volterra equations

David J. Prömel, David Scheffels

The well-posedness is established for multi-dimensional mean-field stochastic Volterra equations with Lipschitz continuous coefficients and allowing for singular kernels as well as…

math.PR2025

A rough path approach to pathwise stochastic integration à la Föllmer

Purba Das, Anna P. Kwossek, David J. Prömel

We develop a general framework for pathwise stochastic integration that extends Föllmer's classical approach beyond gradient-type integrands and standard left-point Riemann sums a…

math.PR2025

Functional differential equations driven by cà dlà g rough paths

Anna P. Kwossek, Andreas Neuenkirch, David J. Prömel

The existence of unique solutions is established for rough differential equations (RDEs) with path-dependent coefficients and driven by cà dlà g rough paths. Moreover, it is shown…

math.PR2024

Hegselmann--Krause model with environmental noise

Li Chen, Paul Nikolaev, David J. Prömel

We study a continuous-time version of the Hegselmann-Krause model describing the opinion dynamics of interacting agents subject to random perturbations. Mathematically speaking, th…