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Multistate Markov models are a canonical parametric approach for data modeling of observed or latent stochastic processes supported on a finite state space. Continuous-time Markov processes describe data that are observed irregularly over…

Semi-Markov processes are a generalization of Markov processes since the exponential distribution of time intervals is replaced with an arbitrary distribution. This paper provides an integro-differential form of the Kolmogorov's backward…

Probability · Mathematics 2017-09-20 Enzo Orsingher , Costantino Ricciuti , Bruno Toaldo

We obtain gradient estimates on solutions to parabolic Kolmogorov equation with singular drift in a large class. Such estimates allow to construct a Feller evolution family, which is used to construct unique weak solutions to the…

Analysis of PDEs · Mathematics 2024-08-13 D. Kinzebulatov , Yu. A. Semenov

Diffusive approximations of Markov jump processes often fail to accurately capture large fluctuations. This is confounding, as the rare events triggered by these large fluctuations, such as the failure of electronic memories, are often the…

Mesoscale and Nanoscale Physics · Physics 2025-12-17 David Roberts , Trevor McCourt , Geremia Massarelli , Jeremy Rothschild , Nahuel Freitas

We introduce and study some backward Kolmogorov equations associated to stochastic filtering problems. Measure-valued processed arise naturally in the context of stochastic filtering and one can formulate two stochastic differential…

Probability · Mathematics 2023-07-19 Mattia Martini

With many Hamiltonians one can naturally associate a |Psi|^2-distributed Markov process. For nonrelativistic quantum mechanics, this process is in fact deterministic, and is known as Bohmian mechanics. For the Hamiltonian of a quantum field…

Quantum Physics · Physics 2007-05-23 Detlef Duerr , Sheldon Goldstein , Roderich Tumulka , Nino Zanghi

We show the variational convergence of an irreversible Markov jump process describing a finite stochastic particle system to the solution of a countable infinite system of deterministic time-inhomogeneous quadratic differential equations…

Analysis of PDEs · Mathematics 2025-07-08 Jasper Hoeksema , Chun Yin Lam , André Schlichting

We formally introduce and study locally-balanced Markov jump processes (LBMJPs) defined on a general state space. These continuous-time stochastic processes with a user-specified limiting distribution are designed for sampling in settings…

Probability · Mathematics 2025-04-21 Samuel Livingstone , Giorgos Vasdekis , Giacomo Zanella

In this article, we consider a Markov-modulated model with jumps for short rate dynamics. We obtain closed formulas for the term structure and forward rates using the properties of the jump-telegraph process and the expectation hypothesis.…

Mathematical Finance · Quantitative Finance 2019-01-11 Oscar Lopez , Gerardo E. Oleaga , Alejandra Sanchez

The goal of this article is to describe the concepts of system dynamics and its applications to the simulation modeling of financial institutions daily activity. The hybrid method of the re-engineering of banking business processes based…

General Finance · Quantitative Finance 2009-12-08 Mikhail I. Rumyantsev

The purpose of this comment is to correct mistaken assumptions and claims made in the paper Stochastic feedback, nonlinear families of Markov processes, and nonlinear Fokker-Planck equations by T. D. Frank. Our comment centers on the claims…

Statistical Mechanics · Physics 2009-11-13 Joseph L. McCauley

We address a class of Markov jump linear systems that are characterized by the underlying Markov process being time-inhomogeneous with a priori unknown transition probabilities. Necessary and sufficient conditions for uniform stochastic…

Systems and Control · Computer Science 2014-11-24 Collin C. Lutz , Daniel J. Stilwell

Markov jump processes are continuous-time stochastic processes with a wide range of applications in both natural and social sciences. Despite their widespread use, inference in these models is highly non-trivial and typically proceeds via…

Machine Learning · Computer Science 2023-06-01 Patrick Seifner , Ramses J. Sanchez

Piecewise-deterministic Markov processes (PDMPs) offer a powerful stochastic modeling framework that combines deterministic trajectories with random perturbations at random times. Estimating their local characteristics (particularly the…

Methodology · Statistics 2025-12-29 Romain Azaïs , Solune Denis

The rigorous linking of exact stochastic models to mean-field approximations is studied. Starting from the differential equation point of view the stochastic model is identified by its Kolmogorov equations, which is a system of linear ODEs…

Dynamical Systems · Mathematics 2011-09-19 András Bátkai , Istvan Z. Kiss , Eszter Sikolya , Péter L. Simon

In this paper, we obtain new drift-type conditions for nonexplosion and explosion for nonhomogeneous Markov pure jump processes in Borel state spaces. The conditions are sharp; e.g., the one for nonexplosion is necessary if the state space…

Probability · Mathematics 2016-11-18 Yi Zhang

Markov jump processes are widely used to model natural and engineered processes. In the context of biological or chemical applications one typically refers to the chemical master equation (CME), which models the evolution of the probability…

Optimization and Control · Mathematics 2017-07-05 Wei Zhang , Carsten Hartmann , Max von Kleist

The paper proposes a class of financial market models which are based on inhomogeneous telegraph processes and jump diffusions with alternating volatilities. It is assumed that the jumps occur when the tendencies and volatilities are…

Pricing of Securities · Quantitative Finance 2008-12-04 Nikita Ratanov

In this paper we study a family of nonlinear (conditional) expectations that can be understood as a semimartingale with uncertain local characteristics. Here, the differential characteristics are prescribed by a time and path-dependent…

Probability · Mathematics 2023-11-07 David Criens , Lars Niemann

Multi-agent systems can be successfully described by kinetic models, which allow one to explore the large scale aggregate trends resulting from elementary microscopic interactions. The latter may be formalised as collision-like rules, in…

Statistical Mechanics · Physics 2020-11-06 Nadia Loy , Andrea Tosin