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We address a class of backward stochastic differential equations on a bounded interval, where the driving noise is a marked, or multivariate, point process. Assuming that the jump times are totally inaccessible and a technical condition…

Probability · Mathematics 2016-06-28 Fulvia Confortola , Marco Fuhrman , Jean Jacod

The chaos expansion of a general non-linear function of a Gaussian stationary increment process conditioned on its past realizations is derived. This work combines Wiener chaos expansion approach to study the dynamics of a stochastic system…

Probability · Mathematics 2018-04-12 Daniel Alpay , Alon Kipnis

We present a detailed study of a simple quantum stochastic process, the quantum phase space Brownian motion, which we obtain as the Markovian limit of a simple model of open quantum system. We show that this physical description of the…

Mathematical Physics · Physics 2015-05-27 Michel Bauer , Denis Bernard

We propose a new multifractional stochastic process which allows for self-exciting behavior, similar to what can be seen for example in earthquakes and other self-organizing phenomena. The process can be seen as an extension of a…

Probability · Mathematics 2019-08-16 Fabian A. Harang , Marc Lagunas-Merino , Salvador Ortiz-Latorre

Stationary stochastic processes with independent increments, of which the Poisson process is a prominent example, are widely used to describe real world events. With the basic assumption that a counting process is stationary and has…

Probability · Mathematics 2018-11-20 Enzhi Li

An explicit first-order drift-randomized Milstein scheme for a regime switching stochastic differential equation is proposed and its bi-stability and rate of strong convergence are investigated for a non-differentiable drift coefficient.…

Probability · Mathematics 2025-03-11 Divyanshu Vashistha , Chaman Kumar

Stochastic differential equations characterized by uncertainty are effective in modelling virus dynamics and provide an alternative to traditional deterministic models. Epidemic models are inevitably subjected to the randomness within the…

Dynamical Systems · Mathematics 2024-08-12 Bishal Chhetri , B. V. Ratish Kumar

Inferring the causal structure underlying stochastic dynamical systems from observational data holds great promise in domains ranging from science and health to finance. Such processes can often be accurately modeled via stochastic…

Machine Learning · Computer Science 2025-03-04 Georg Manten , Cecilia Casolo , Emilio Ferrucci , Søren Wengel Mogensen , Cristopher Salvi , Niki Kilbertus

In this paper a drift-randomized Milstein method is introduced for the numerical solution of non-autonomous stochastic differential equations with non-differentiable drift coefficient functions. Compared to standard Milstein-type methods we…

Numerical Analysis · Mathematics 2018-12-12 Raphael Kruse , Yue Wu

For a zero-sum stochastic game which does not satisfy the Isaacs condition, we provide a value function representation for an Isaacs-type equation whose Hamiltonian lies in between the lower and upper Hamiltonians, as a convex combination…

Probability · Mathematics 2016-09-30 Daniel Hernández-Hernández , Mihai Sîrbu

We introduce Conformal Interquantile Regression (CIR), a conformal regression method that efficiently constructs near-minimal prediction intervals with guaranteed coverage. CIR leverages black-box machine learning models to estimate outcome…

Machine Learning · Statistics 2026-01-07 Naixin Guo , Rui Luo , Zhixin Zhou

We consider a fractional Brownian motion with unknown linear drift such that the drift coefficient has a prior normal distribution and construct a sequential test for the hypothesis that the drift is positive versus the alternative that it…

Statistics Theory · Mathematics 2026-01-14 Alexey Muravlev , Mikhail Zhitlukhin

Stochastic dynamical systems allow modelling of transitions induced by disturbances, in particular from an attracting equilibrium and crossing the stable manifold of a saddle. In the small-noise limit, the probability of such transitions is…

Statistical Mechanics · Physics 2025-09-05 Jiayao Shao , Tobias Grafke , Robert S. MacKay

We consider a system of stochastic differential equations driven by a standard n-dimensional Brownian motion where the drift coefficient satisfies a Novikov-type condition while the diffusion coefficient is the identity matrix. We define a…

Probability · Mathematics 2013-07-15 Alberto Lanconelli

In this work, we propose the balanced implicit method (BIM) to approximate the solution of the delay Cox-Ingersoll-Ross (CIR) model with jump which often gives rise to model an asset price and stochastic volatility . We show that this…

Probability · Mathematics 2017-12-11 A. S. Fatemion Aghdas , Seyed Mohammad Hossein , Mahdieh Tahmasebi

In this paper we study regularity estimates for the solution to an obstacle problem arising in stochastic impulse control theory. We prove using elementary methods the known sharp $C_{loc}^{1,1}$ estimate for the solution. The new proof is…

Analysis of PDEs · Mathematics 2016-12-02 Rohit Jain

In this note we consider a class of neutral stochastic functional differential equations with finite delay driven simultaneously by a fractional Brownian motion and a Poisson point processes in a Hilbert space. We prove an existence and…

Dynamical Systems · Mathematics 2013-12-25 S. Hajji , E. Lakhel

Sufficient and necessary conditions are presented for the order-preservation of stochastic functional differential equations on $\R^d$ with non-Lipschitzian coefficients driven by the Brownian motion and Poisson processes. The sufficiency…

Probability · Mathematics 2014-01-22 Xing Huang , Feng-Yu Wang

We consider a continuous time random walk on the two-dimensional discrete torus, whose motion is governed by the discrete Gaussian free field on the corresponding box acting as a potential. More precisely, at any vertex the walk waits an…

Probability · Mathematics 2018-06-19 Aser Cortines , Julian Gold , Oren Louidor

The master equation for a linear open quantum system in a general environment is derived using a stochastic approach. This is an alternative derivation to that of Hu, Paz and Zhang, which was based on the direct computation of path…

General Relativity and Quantum Cosmology · Physics 2011-08-04 Esteban Calzetta , Albert Roura , Enric Verdaguer