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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

The almost sure rate of exponential-polynomial growth or decay of affine stochastic Volterra and affine stochastic finite-delay equations is investigated. These results are achieved under suitable smallness conditions on the intensities of…

Classical Analysis and ODEs · Mathematics 2013-10-10 John A. D. Appleby , John A. Daniels

In this paper we study jump-diffusion stochastic differential equations (SDEs) with a discontinuous drift coefficient and a possibly degenerate diffusion coefficient. Such SDEs appear in applications such as optimal control problems in…

Numerical Analysis · Mathematics 2021-01-15 Paweł Przybyłowicz , Michaela Szölgyenyi

This paper studies the numerical methods to approximate the solutions for a sort of McKean-Vlasov neutral stochastic differential delay equations (MV-NSDDEs) that the growth of the drift coefficients is super-linear. First, We obtain that…

Probability · Mathematics 2022-11-04 Yuanping Cui , Xiaoyue Li , Yi Liu , Chenggui Yuan

In this paper, we consider a class of stochastic differential equations driven by symmetric non-degenerate $\alpha$-stable processes (including cylindrical ones) with $\alpha \in (1,2)$. We first establish a quantitative estimate for the…

Probability · Mathematics 2026-04-10 Zimo Hao , Mingyan Wu

For backward stochastic Volterra integral equations (BSVIEs) in multi-dimensional Euclidean spaces, comparison theorems are established in a systematic way for the adapted solutions and adapted M-solutions. For completeness, comparison…

Probability · Mathematics 2012-08-13 Tianxiao Wang , Jiongmin Yong

We study stochastic volatility models in which the volatility process is a positive continuous function of a continuous Volterra stochastic process. We state some pathwise large deviation principles for the scaled log-price.

Probability · Mathematics 2020-01-31 M. Cellupica , B. Pacchiarotti

We present an explicit numerical approximation scheme, denoted by $\{X^n\}$, for the effective simulation of solutions $X$ to a multivariate stochastic differential equation (SDE) with a superlinearly growing $\kappa$-dissipative drift,…

Probability · Mathematics 2026-01-21 Olga Aryasova , Oleksii Kulyk , Ilya Pavlyukevich

Semilinear hyperbolic stochastic partial differential equations (SPDEs) find widespread applications in the natural and engineering sciences. However, the traditional Gaussian setting may prove too restrictive, as phenomena in mathematical…

Numerical Analysis · Mathematics 2023-07-04 Andrea Barth , Andreas Stein

In this paper, we study a class of backward stochastic Volterra integral equations driven by Teugels martingales associated with an independent L\'{e}vy process and an independent Brownian motion (BSVIELs). We prove the existence and…

Probability · Mathematics 2016-03-11 Wen Lu

We present two fully probabilistic Euler schemes, one explicit and one implicit, for the simulation of McKean-Vlasov Stochastic Differential Equations (MV-SDEs) with drifts of super-linear growth and random initial condition. We provide a…

Probability · Mathematics 2020-12-29 G. dos Reis , S. Engelhardt , G. Smith

Firstly, we investigate Euler-Maruyama approximation for solutions of stochastic differential equations (SDEs) driven by a symmetric \alpha\ stable process under Komatsu condition for coefficients. The approximation implies naturally the…

Probability · Mathematics 2011-10-13 Hiroya Hashimoto

This paper is concerned with a unified treatment of linear quadratic control problem for stochastic Volterra integral equations (SVIEs), motivated by the various approaches and scattered results in the existing literature. A novel class of…

Optimization and Control · Mathematics 2024-12-13 Jiayin Gong , Tianxiao Wang

We present an implicit Split-Step explicit Euler type Method (dubbed SSM) for the simulation of McKean-Vlasov Stochastic Differential Equations (MV-SDEs) with drifts of superlinear growth in space, Lipschitz in measure and non-constant…

Numerical Analysis · Mathematics 2022-05-10 Xingyuan Chen , Goncalo dos Reis

In this paper we study the stochastic inhomogeneous incompressible Euler equations in the whole space $\RR^3$. We prove the existence and pathwise uniqueness of local solutions with both additive and multiplicative stochastic noise. Our…

Analysis of PDEs · Mathematics 2025-10-28 Claudia Espitia , David A. C. Mollinedo , Christian Olivera

This paper develops and analyzes a fully discrete finite element method for a class of semilinear stochastic partial differential equations (SPDEs) with multiplicative noise. The nonlinearity in the diffusion term of the SPDEs is assumed to…

Numerical Analysis · Mathematics 2018-11-22 Xiaobing Feng , Yukun Li , Yi Zhang

The strong convergence of Euler approximations of stochastic delay differential equations is proved under general conditions. The assumptions on drift and diffusion coefficients have been relaxed to include polynomial growth and only…

Probability · Mathematics 2013-03-07 Chaman Kumar , Sotirios Sabanis

We provide explicit series expansions to certain stochastic path-dependent integral equations in terms of the path signature of the time augmented driving Brownian motion. Our framework encompasses a large class of stochastic linear…

Probability · Mathematics 2025-11-04 Eduardo Abi Jaber , Louis-Amand Gérard , Yuxing Huang

We obtain general weak existence and stability results for stochastic convolution equations with jumps under mild regularity assumptions, allowing for non-Lipschitz coefficients and singular kernels. Our approach relies on weak convergence…

Probability · Mathematics 2021-12-22 Eduardo Abi Jaber , Christa Cuchiero , Martin Larsson , Sergio Pulido

We survey recent developments in the field of complexity of pathwise approximation in $p$-th mean of the solution of a stochastic differential equation at the final time based on finitely many evaluations of the driving Brownian motion.…

Probability · Mathematics 2024-03-04 T. Müller-Gronbach , L. Yaroslavtseva