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We provide a unified treatment of pathwise Large and Moderate deviations principles for a general class of multidimensional stochastic Volterra equations with singular kernels, not necessarily of convolution form. Our methodology is based…

Probability · Mathematics 2022-04-15 Antoine Jacquier , Alexandre Pannier

We study fractional stochastic volatility models in which the volatility process is a positive continuous function $\sigma$ of a continuous Gaussian process $\widehat{B}$. Forde and Zhang established a large deviation principle for the…

Mathematical Finance · Quantitative Finance 2018-08-06 Archil Gulisashvili

Using a weak convergence approach, we establish a Large Deviation Principle (LDP) for the solutions of fluid dynamic systems in two-dimensional bounded domains subjected to no-slip boundary conditions and perturbed by additive noise. Our…

Probability · Mathematics 2023-05-19 Federico Butori , Eliseo Luongo

In this article, we established a large deviation principle for invariant measures of solutions of stochastic partial differential equations with two reflecting walls driven by space-time white noise.

Probability · Mathematics 2012-04-02 Tusheng Zhang

We obtain large deviations theorems for nonconventional sums with underlying process being a Markov process satisfying the Doeblin condition or a dynamical system such as subshift of finite type or hyperbolic or expanding transformation.

Probability · Mathematics 2013-02-21 Yuri Kifer , S. R. S. Varadhan

Shot noise processes are used in applied probability to model a variety of physical systems in, for example, teletraffic theory, insurance and risk theory and in the engineering sciences. In this work we prove a large deviation principle…

Probability · Mathematics 2016-04-18 Amarjit Budhiraja , Pierre Nyquist

Using the hyper-exponential recurrence criterion, a large deviation principle for the occupation measure is derived for a class of non-linear monotone stochastic partial differential equations. The main results are applied to many concrete…

Probability · Mathematics 2016-01-26 Ran Wang , Jie Xiong , Lihu Xu

Spike variation technique plays a crucial role in deriving Pontryagin's type maximum principle of optimal controls for differential equations of several types, including ordinary differential equations (ODEs), partial differential equations…

Optimization and Control · Mathematics 2022-09-13 Tianxiao Wang , Jiongmin Yong

In this paper, the strong averaging principle is researched for a class of H\"{o}lder continuous drift slow-fast SPDEs with $\alpha$-stable process by the Zvonkin's transformation and the classical Khasminkii's time discretization method.…

Probability · Mathematics 2021-05-11 Xiaobin Sun , Huilian Xia , Yingchao Xie , Xingcheng Zhou

In this paper, we established the Freidlin-Wentzell type large deviation principles for first-order scalar conservation laws perturbed by small multiplicative noise. Due to the lack of the viscous terms in the stochastic equations, the…

Probability · Mathematics 2020-03-24 Zhao Dong , Jiang-Lun Wu , Rangrang Zhang , Tusheng Zhang

We study stochastic volatility models in which the volatility process is a function of a continuous fractional stochastic process, which is an integral transform of the solution of an SDE satisfying the Yamada-Watanabe condition. We…

Probability · Mathematics 2020-03-31 Stefan Gerhold , Christoph Gerstenecker , Archil Gulisashvili

In this article we introduce a new method for the construction of unique strong solutions of a larger class of stochastic delay equations driven by a discontinuous drift vector field and a Wiener process. The results obtained in this paper…

Probability · Mathematics 2017-09-22 D. Baños , H. H. Haferkorn , F. Proske

We prove the small-noise large deviation principle for the three-dimensional primitive equations with transport noise and turbulent pressure. Transport noise is important for geophysical fluid dynamics applications, as it takes into account…

Probability · Mathematics 2025-12-23 Antonio Agresti , Esmée Theewis

We study a precise large deviation principle for a stationary regularly varying sequence of random variables. This principle extends the classical results of A.V. Nagaev (1969) and S.V. Nagaev (1979) for iid regularly varying sequences. The…

Statistics Theory · Mathematics 2012-06-11 Thomas Mikosch , Olivier Wintenberger

We study small noise large deviation asymptotics for stochastic differential equations with a multiplicative noise given as a fractional Brownian motion $B^H$ with Hurst parameter $H>\frac12$. The solutions of the stochastic differential…

Probability · Mathematics 2020-06-18 Amarjit Budhiraja , Xiaoming Song

In this paper, we study the averaging principle for distribution dependent stochastic differential equations with drift in localized $L^p$ spaces. Using Zvonkin's transformation and estimates for solutions to Kolmogorov equations, we prove…

Probability · Mathematics 2022-10-27 Mengyu Cheng , Zimo Hao , Michael Röckner

In this paper, we aim to study the asymptotic behavior for multi-scale McKean-Vlasov stochastic dynamical systems. Firstly, we obtain a central limit type theorem, i.e, the deviation between the slow component $X^{\varepsilon}$ and the…

Probability · Mathematics 2023-06-02 Wei Hong , Shihu Li , Wei Liu , Xiaobin Sun

We investigate periodic points of the Dyck shift from the viewpoint of large deviations. We establish the level-2 Large Deviation Principle with the rate function given in terms of Kolmogorov-Sinai entropies of shift-invariant Borel…

Dynamical Systems · Mathematics 2025-03-19 Hiroki Takahasi

In this paper, we consider a kind of fully coupled slow fast motion, in which the slow variable satisfies the non Lipschitz condition. We prove that the stochastic flow of the slow variable exists and moreover, satisfies the large deviation…

Probability · Mathematics 2024-09-20 Mingkun Ye , Zuozheng Zhang

In this paper, we establish a large deviation principle for the solutions to the stochastic heat equations with logarithmic nonlinearity driven by Brownian motion, which is neither locally Lipschitz nor locally monotone. Nonlinear versions…

Probability · Mathematics 2022-07-07 Tianyi Pan , Shijie Shang , Tusheng Zhang