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We consider a large market model of defaultable assets in which the asset price processes are modelled as Heston-type stochastic volatility models with default upon hitting a lower boundary. We assume that both the asset prices and their…

Probability · Mathematics 2019-05-15 Ben Hambly , Nikolaos Kolliopoulos

Many models of population dynamics are formulated as deterministic iterated maps although real populations are stochastic. This is justifiable in the limit of large population sizes, as the stochastic fluctuations are negligible then.…

Populations and Evolution · Quantitative Biology 2025-09-16 Snehal M. Shekatkar

In this note we prove an existence and uniqueness result of solution for multidimensional delay differential equations with normal reflection and driven by a H\"older continuous function of order $\beta \in (\frac13,\frac12)$. We also…

Probability · Mathematics 2012-05-18 Mireia Besalú , David Márquez-Carreras , Carles Rovira

In this paper, we investigate the stochastic evolution equations (SEEs) driven by $\log$-Whittle-Mat$\acute{{\mathrm{e}}}$rn (W-M) random diffusion coefficient field and $Q$-Wiener multiplicative force noise. First, the well-posedness of…

Numerical Analysis · Mathematics 2022-07-05 X. Qi , M. Azaiez , C. Huang , C. Xu

We consider the problem of forecasting complex, nonlinear space-time processes when observations provide only partial information of on the system's state. We propose a natural data-driven framework, where the system's dynamics are modelled…

Systems and Control · Computer Science 2019-03-01 Ibrahim Ayed , Emmanuel de Bézenac , Arthur Pajot , Julien Brajard , Patrick Gallinari

In this paper we investigate stability of travelling wave solutions to a class of reaction-diffusion equations perturbed by infinite-dimensional additive noise with H\"older continuous paths, covering in particular fractional Brownian…

Probability · Mathematics 2026-01-12 Amjad Saef , Wilhelm Stannat

We consider stochastic differential equation $$ d X_t=b(X_t) dt +d W_t^H, $$ where the drift $b$ is either a measure or an integrable function, and $W^H$ is a $d$-dimensional fractional Brownian motion with Hurst parameter $H\in(0,1)$,…

Probability · Mathematics 2025-10-22 Oleg Butkovsky , Khoa Lê , Leonid Mytnik

In this paper, we are concerned with multi-scale distribution dependent stochastic differential equations driven by fractional Brownian motion (with Hurst index $H>\frac12$ and standard Brownian motion, simultaneously. Our aim is to…

Probability · Mathematics 2023-06-12 Shen Gunagjun , Zhou Huan , Wu Jianglun

We investigate the stabilization of unstable multidimensional partially observed single-sensor and multi-sensor linear systems driven by unbounded noise and controlled over discrete noiseless channels under fixed-rate information…

Optimization and Control · Mathematics 2012-09-21 Andrew P. Johnston , Serdar Yüksel

We investigate mild solutions for stochastic evolution equations driven by a fractional Brownian motion (fBm) with Hurst parameter H in (1/3, 1/2] in infinite-dimensional Banach spaces. Using elements from rough paths theory we introduce an…

Probability · Mathematics 2019-04-08 Robert Hesse , Alexandra Neamtu

We prove an existence and uniqueness theorem for solutions of multidimensional, time dependent, stochastic differential equations driven simultaneously by a multidimensional fractional Brownian motion with Hurst parameter H>1/2 and a…

Probability · Mathematics 2022-01-27 João Guerra , David Nualart

This article deals with invariant manifolds for infinite dimensional random dynamical systems with different time scales. Such a random system is generated by a coupled system of fast-slow stochastic evolutionary equations. Under suitable…

Probability · Mathematics 2013-07-29 Hongbo Fu , Xianming Liu , Jinqiao Duan

We investigate the three-dimensional fractionally dissipated primitive equations with transport noise, focusing on subcritical and critical dissipation regimes characterized by $ (-\Delta)^{s/2} $ with $ s \in (1,2)$ and $s = 1$,…

Analysis of PDEs · Mathematics 2025-01-20 Ruimeng Hu , Quyuan Lin , Rongchang Liu

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are…

Populations and Evolution · Quantitative Biology 2018-07-19 George W. A. Constable , Alan J. McKane

Stochastic differential equations and stochastic dynamics are good models to describe stochastic phenomena in real world. In this paper, we study N independent stochastic processes Xi(t) with real entries and the processes are determined by…

Statistics Theory · Mathematics 2020-01-07 Min Dai , Jinqiao Duan , Junjun Liao , Xiangjun Wang

We find an explicit expression for the cross-covariance between stochastic integral processes with respect to a $d$-dimensional fractional Brownian motion (fBm) $B_t$ with Hurst parameter $H>1/2$, where the integrands are vector fields…

Probability · Mathematics 2016-12-16 Yohaï Maayan , Eddy Mayer-Wolf

For stochastic evolution equations with fractional derivatives, classical solutions exist when the order of the time derivative of the unknown function is not too small compared to the order of the time derivative of the noise; otherwise,…

Probability · Mathematics 2018-11-01 Sergey V. Lototsky , Boris L. Rozovsky

A stochastic differential equation with coefficients defined in a scale of Hilbert spaces is considered. The existence and uniqueness of finite time solutions is proved by an extension of the Ovsyannikov method. This result is applied to a…

Functional Analysis · Mathematics 2018-05-15 Alexei Daletskii

Complex dynamical systems which are governed by anomalous diffusion often can be described by Langevin equations driven by L\'evy stable noise. In this article we generalize nonlinear stochastic differential equations driven by Gaussian…

Statistical Mechanics · Physics 2015-06-18 Rytis Kazakevicius , Julius Ruseckas

We consider the problem of learning stabilizable systems governed by nonlinear state equation $h_{t+1}=\phi(h_t,u_t;\theta)+w_t$. Here $\theta$ is the unknown system dynamics, $h_t $ is the state, $u_t$ is the input and $w_t$ is the…

Machine Learning · Computer Science 2021-11-22 Yahya Sattar , Samet Oymak