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We construct the basis of a stochastic calculus for so-called Volterra processes, i.e., processes which are defined as the stochastic integral of a time-dependent kernel with respect to a standard Brownian motion. For these processes which…

Probability · Mathematics 2007-05-23 L. Decreusefond

We treat a stochastic integration theory for a class of Hilbert-valued, volatility-modulated, conditionally Gaussian Volterra processes. We apply techniques from Malliavin calculus to define this stochastic integration as a sum of a…

Probability · Mathematics 2016-03-18 Fred Espen Benth , André Süß

This papers develops a stochastic integration theory with respect to volatility modulated L\'{e}vy-driven Volterra (VMLV) processes. It extends recent results in the literature to allow for stochastic volatility and pure jump processes in…

Probability · Mathematics 2012-05-16 Ole E. Barndorff-Nielsen , Fred Espen Benth , Jan Pedersen , Almut E. D. Veraart

We introduce a pathwise integration for Volterra processes driven by L\'evy noise or martingale noise. These processes are widely used in applications to turbulence, signal processes, biology, and in environmental finance. Indeed they…

Probability · Mathematics 2016-08-31 Giulia Di Nunno , Yuliya Mishura , Konstiantyn Ralchenko

Stochastic integration with respect to Gaussian processes, such as fractional Brownian motion (fBm) or multifractional Brownian motion (mBm), has raised strong interest in recent years, motivated in particular by applications in finance,…

Probability · Mathematics 2018-02-15 Joachim Lebovits

We study the regular conditional law of mixed Gaussian Volterra processes under the influence of model disturbances. More precisely, we study prediction of Gaussian Volterra processes driven by a Brownian motion in a case where the Brownian…

Probability · Mathematics 2019-04-23 Tommi Sottinen , Lauri Viitasaari

Given a Gaussian stationary increment processes with spectral density, we show that a Wick-Ito integral with respect to this process can be naturally obtained using Hida's white noise space theory. We use the Bochner-Minlos theorem to…

Probability · Mathematics 2012-02-09 Daniel Alpay , Alon Kipnis

We study the existence and uniqueness of solutions to stochastic differential equations with Volterra processes driven by L\'evy noise. For this purpose, we study in detail smoothness properties of these processes. Special attention is…

Probability · Mathematics 2020-08-26 Giulia Di Nunno , Yuliya Mishura , Kostiantyn Ralchenko

In this paper we investigate a problem of large deviations for continuous Volterra processes under the influence of model disturbances. More precisely, we study the behavior, in the near future after $T$, of a Volterra process driven by a…

Probability · Mathematics 2020-03-30 Barbara Pacchiarotti

Stochastic integration \textit{wrt} Gaussian processes has raised strong interest in recent years, motivated in particular by its applications in Internet traffic modeling, biomedicine and finance. The aim of this work is to define and…

Probability · Mathematics 2018-02-15 Joachim Lebovits

We introduce the Volterra Stein-Stein model with stochastic interest rates, where both volatility and interest rates are driven by correlated Gaussian Volterra processes. This framework unifies various well-known Markovian and non-Markovian…

Mathematical Finance · Quantitative Finance 2025-07-17 Eduardo Abi Jaber , Donatien Hainaut , Edouard Motte

This paper examines the cycling behavior of a deterministic and a stochastic version of the economic interpretation of the Lotka-Volterra model, the Goodwin model. We provide a characterization of orbits in the deterministic highly…

Dynamical Systems · Mathematics 2014-02-03 Bernardo Costa-Lima , Adrien Nguyen Huu

We investigate the probabilistic and analytic properties of Volterra processes constructed as pathwise integrals of deterministic kernels with respect to the H\"older continuous trajectories of Hilbert-valued Gaussian processes. To this…

Probability · Mathematics 2020-06-01 Fred E. Benth , Fabian A. Harang

A fast simulation framework for stochastic Volterra processes based on Random Fourier Features (RFF) approximation of the kernel is developed. After recalling the main properties of Volterra processes and reviewing existing numerical…

Mathematical Finance · Quantitative Finance 2026-05-26 Othmane Zarhali , Nicolas Langrené

We consider a stochastic Volterra integral equation with regular path-dependent coefficients and a Brownian motion as integrator in a multidimensional setting. Under an imposed absolute continuity condition, the unique solution is a…

Probability · Mathematics 2021-03-29 Alexander Kalinin

This paper introduces a comprehensive extension of the path integral formalism to model stochastic processes with arbitrary multiplicative noise. To do so, It\^o diffusive process is generalized by incorporating a multiplicative noise term…

Mathematical Physics · Physics 2025-03-06 F. S. Abril-Bermúdez , C. J. Quimbay , J. E. Trinidad-Segovia , M. A Sánchez-Granero

We study the problem of optimal inside control of a stochastic Volterra equation driven by a Brownian motion and a Poisson random measure. We prove a sufficient and a necessary maximum principle for the optimal control when the trader has…

Optimization and Control · Mathematics 2017-03-28 Olfa Draouil

With the use of Hida's white noise space theory space theory and spaces of stochastic distributions, we present a detailed analytic continuation theory for classes of Gaussian processes, with focus here on Brownian motion. For the latter,…

Probability · Mathematics 2025-01-27 Luis Daniel Abreu , Daniel Alpay , Tryphon Georgiou , Palle Jorgensen

We consider convolution-type stochastic Volterra equations with additive Hilbert-valued fractional Brownian motion, $0<H<1$. We find the weak solution to this stochastic Volterra equation, and study its stochastic integral part, the…

Probability · Mathematics 2007-05-23 Peter Caithamer , Anna Karczewska

Motivated by the traditional Lotka-Volterra competitive models, this paper proposes and analyzes a class of stochastic reaction-diffusion partial differential equations. In contrast to the models in the literature, the new formulation…

Probability · Mathematics 2021-05-10 N. N. Nguyen , G. Yin
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