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Stochastic differential equations (SDEs) using jump-diffusion processes describe many natural phenomena at the microscopic level. Since they are commonly used to model economic and financial evolutions, the calibration and optimal control…

Optimization and Control · Mathematics 2025-05-08 Jan Bartsch , Alfio Borzi , Gabriele Ciaramella , Jan Reichle

Literature is full of inference techniques developed to estimate the parameters of stochastic dynamical systems driven by the well-known Brownian noise. Such diffusion models are often inappropriate models to properly describe the dynamics…

Dynamical Systems · Mathematics 2024-02-19 Babak M. S. Arani

We study stochastic equations of non-negative processes with jumps. The existence and uniqueness of strong solutions are established under Lipschitz and non-Lipschitz conditions. The comparison property of two solutions are proved under…

Probability · Mathematics 2008-02-08 Zongfei Fu , Zenghu Li

We present the first higher-order approximation scheme for solutions of jump-diffusion stochastic differential equations with discontinuous drift. For this transformation-based jump-adapted quasi-Milstein scheme we prove $L^p$-convergence…

Numerical Analysis · Mathematics 2023-12-06 Paweł Przybyłowicz , Verena Schwarz , Michaela Szölgyenyi

In this article we consider parametric Bayesian inference for stochastic differential equations (SDE) driven by a pure-jump stable Levy process, which is observed at high frequency. In most cases of practical interest, the likelihood…

Statistics Theory · Mathematics 2017-07-28 Ajay Jasra , Kengo Kamatani , Hiroki Masuda

This work investigates the strong and weak convergence orders of numerical methods for SDEs driven by time-changed L\'{e}vy noise under the globally Lipschitz conditions. Based on the duality theorem, we prove that the numerical…

Numerical Analysis · Mathematics 2025-04-29 Ziheng Chen , Jiao Liu , Anxin Wu

We consider high frequency samples from ergodic L\'evy driven stochastic differential equation (SDE) with drift coefficient $a(x,\alpha)$ and scale coefficient $c(x,\gamma)$ involving unknown parameters $\alpha$ and $\gamma$. We suppose…

Statistics Theory · Mathematics 2016-01-12 Hiroki Masuda , Yuma Uehara

Stochastic Differential Equations (SDEs) were originally devised by It\^o to provide a pathwise construction of diffusion processes. A less explored approach to represent them is through Time Change Equations (TCEs) as put forth by Doeblin.…

Probability · Mathematics 2024-03-25 Miriam Ramírez , Gerónimo Uribe Bravo

We prove smoothing properties of nonlocal transition semigroups associated to a class of stochastic differential equations (SDE) driven by additive pure-jump L\'evy noise. In particular, we assume that the L\'evy process driving the SDE is…

Probability · Mathematics 2012-08-15 Seiichiro Kusuoka , Carlo Marinelli

We study SDE $$ d X_t = b(X_t) \, dt + A(X_{t-}) \, d Z_t, \quad X_{0} = x \in \mathbb{R}^d, \quad t \geq 0 $$ where $Z=(Z^1, \dots, Z^d)^T$, with $Z^i, i=1,\dots, d$ being independent one-dimensional symmetric jump L\'evy processes, not…

Probability · Mathematics 2022-08-16 Tadeusz Kulczycki , Oleksii Kulyk , Michał Ryznar

The work is about multiscale stochastic dynamical systems driven by L\'evy processes. First, we prove that these systems can approximate low-dimensional systems on random invariant manifolds. Second, we establish that nonlinear filterings…

Probability · Mathematics 2020-03-26 Huijie Qiao

We will introduce Euler-Maruyama approximations given by an orthogonal system in $L^{2}[0,1]$ for high dimensional SDEs, which could be finite dimensional approximations of SPDEs. In general, the higher the dimension is, the more one needs…

Probability · Mathematics 2021-04-06 Jirô Akahori , Masahiro Kinuya , Takashi Sawai , Tomooki Yuasa

We develop the method of stochastic modified equations (SME), in which stochastic gradient algorithms are approximated in the weak sense by continuous-time stochastic differential equations. We exploit the continuous formulation together…

Machine Learning · Computer Science 2017-06-21 Qianxiao Li , Cheng Tai , Weinan E

In this paper, we study the asymptotic behavior for multi-scale stochastic differential equations driven by L\'evy processes. The optimal strong convergence order 1/2 is obtained by studying the regularity estimates for the solution of…

Probability · Mathematics 2023-09-26 Yinghui Shi , Xiaobin Sun , Liqiong Wang , Yingchao Xie

The problem of drift estimation for the solution $X$ of a stochastic differential equation with L\'evy-type jumps is considered under discrete high-frequency observations with a growing observation window. An efficient and asymptotically…

Statistics Theory · Mathematics 2016-03-18 Arnaud Gloter , Dasha Loukianova , Hilmar Mai

The weak variance-alpha-gamma process is a multivariate L\'evy process constructed by weakly subordinating Brownian motion, possibly with correlated components with an alpha-gamma subordinator. It generalises the variance-alpha-gamma…

Methodology · Statistics 2018-07-30 Boris Buchmann , Kevin W. Lu , Dilip B. Madan

In this paper we discuss the possibility of using multilevel Monte Carlo (MLMC) methods for weak approximation schemes. It turns out that by means of a simple coupling between consecutive time discretisation levels, one can achieve the same…

Computational Finance · Quantitative Finance 2014-10-07 Denis Belomestny , Tigran Nagapetyan

In this paper, we solve exit problems for a L\'evy process that resets proportionally to its current position at independent Poisson epochs times. This resetting causes an additional (proportional to its current level) downward (upward)…

Probability · Mathematics 2026-05-29 Zbigniew Palmowski , Noah Beelders , Lewis Ramsden , Apostolos D. Papaioannou

We study the existence and uniqueness, the regularity, and the long-time behavior of strong solutions to stochastic curve shortening flow driven by a transport-type pure jump L\'evy noise. To obtain the existence and uniqueness of strong…

Probability · Mathematics 2026-05-12 Xiaotian Ge , Shijie Shang , Weina Wu , Jianliang Zhai

This paper presents a proximal-point-based catalyst scheme for simple first-order methods applied to convex minimization and convex-concave minimax problems. In particular, for smooth and (strongly)-convex minimization problems, the…

Optimization and Control · Mathematics 2023-11-09 Guanghui Lan , Yan Li
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