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Related papers: Pathwise construction of affine processes

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A Markov Additive Process is a bi-variate Markov process $(\xi,J)=\big((\xi_t,J_t),t\geq0\big)$ which should be thought of as a multi-type L\'evy process: the second component $J$ is a Markov chain on a finite space $\{1,\ldots,K\}$, and…

Probability · Mathematics 2018-10-04 Robin Stephenson

We investigate the iterative methods proposed by Maz'ya and Kozlov (see [KM1], [KM2]) for solving ill-posed inverse problems modeled by partial differential equations. We consider linear evolutionary problems of elliptic, hyperbolic and…

Numerical Analysis · Mathematics 2020-12-01 J. Baumeister , A. Leitao

We develop a one-dimensional notion of affine processes under parameter uncertainty, which we call non-linear affine processes. This is done as follows: given a set of parameters for the process, we construct a corresponding non-linear…

Probability · Mathematics 2019-03-27 Tolulope Fadina , Ariel Neufeld , Thorsten Schmidt

We study nonlinear time-inhomogeneous Markov processes in the sense of McKean's seminal work [32]. These are given as families of laws $\mathbb{P}_{s,\zeta}$, $s\geq 0$, on path space, where $\zeta$ runs through a set of admissible initial…

Probability · Mathematics 2024-10-21 Marco Rehmeier , Michael Röckner

Many biological and medical questions can be modeled using time-to-event data in finite-state Markov chains, with the phase-type distribution describing intervals between events. We solve the inverse problem: given a phase-type…

Dynamical Systems · Mathematics 2024-11-19 Ovidiu Radulescu , Dima Grigoriev , Matthias Seiss , Maria Douaihy , Mounia Lagha , Edouard Bertrand

Any exchangeable Markov processes on $[k]^{\mathbb{N}}$ with cadlag sample paths projects to a Markov process on the simplex whose sample paths are cadlag and of locally bounded variation. Furthermore, any such process has a de Finetti-type…

Probability · Mathematics 2013-11-22 Harry Crane , Steven P. Lalley

We derive a moment formula for generalized fractional polynomial processes, i.e., for polynomial-preserving Markov processes time-changed by an inverse L\'evy-subordinator. If the time change is inverse $\alpha$-stable, the time-derivative…

Probability · Mathematics 2026-02-27 Johannes Assefa , Martin Keller-Ressel

Monotone L\'evy processes with additive increments are defined and studied. It is shown that these processes have a natural Markov structure and their Markov transition semigroups are characterized using the monotone L\'evy-Khintchine…

Probability · Mathematics 2021-04-21 Uwe Franz , Naofumi Muraki

We study Markov processes conditioned so that their local time must grow slower than a prescribed function. Building upon recent work on Brownian motion with constrained local time in [5] and [33], we study transience and recurrence for a…

Probability · Mathematics 2020-12-24 Adam Barker

We develop a convergent variational perturbation theory for conditional probability densities of Markov processes. The power of the theory is illustrated by applying it to the diffusion of a particle in an anharmonic potential.

Condensed Matter · Physics 2009-11-07 Hagen Kleinert , Axel Pelster , Mihai V. Putz

In the paper we consider some piecewise deterministic Markov process whose continuous component evolves according to semiflows, which are switched at the jump times of a Poisson process. The associated Markov chain describes the states of…

Probability · Mathematics 2023-10-06 Dawid Czapla , Sander C. Hille , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

Among the various critical systems that worth to be formally analyzed, a wide set consists of controllers for dynamical systems. Those programs typically execute an infinite loop in which simple com putations update internal states and…

Optimization and Control · Mathematics 2014-09-18 Assalé Adje , Pierre-Loïc Garoche

When is it possible to interpret a given Markov process as a L\'evy-like process? Since the class of L\'evy processes can be defined by the relation between transition probabilities and convolutions, the answer to this question lies in the…

Probability · Mathematics 2020-09-08 Rúben Sousa , Manuel Guerra , Semyon Yakubovich

For Markov processes evolving on multiple time-scales a combination of large component scalings and averaging of rapid fluctuations can lead to useful limits for model approximation. A general approach to proving a law of large numbers to a…

Probability · Mathematics 2020-12-29 Lea Popovic

We provide a general framework for dual representations of Laplace transforms of Markov processes. Such representations state that the Laplace transform of a finite-dimensional distribution of a Markov process can be expressed in terms of a…

Probability · Mathematics 2024-10-29 Alexey Kuznetsov , Yizao Wang

We construct a family of genealogy-valued Markov processes that are induced by a continuous-time Markov population process. We derive exact expressions for the likelihood of a given genealogy conditional on the history of the underlying…

Probability · Mathematics 2022-01-26 Aaron A. King , Qianying Lin , Edward L. Ionides

We consider a stochastically continuous, affine Markov process in the sense of Duffie, Filipovic and Schachermayer, with cadlag paths, on a general state space D, i.e. an arbitrary Borel subset of R^d. We show that such a process is always…

Probability · Mathematics 2012-05-23 Martin Keller-Ressel , Walter Schachermayer , Josef Teichmann

Let f,g be two algebraically independent regular functions from the smooth affine complex variety U to the affine line. The associated exponential Gauss-Manin systems on the affine line are defined to be the cohomology sheaves of the direct…

Algebraic Geometry · Mathematics 2007-05-23 Marco Hien , Celine Roucairol

This paper develops a systematic treatment of monotonicity-based pathwise dualities for Markov processes taking values in partially ordered sets. We show that every Markov process that takes values in a finite partially ordered set and…

Probability · Mathematics 2016-10-26 Anja Sturm , Jan M. Swart

In this work we consider one-dimensional generalized affine processes under the paradigm of Knightian uncertainty (so-called non-linear generalized affine models). This extends and generalizes previous results in Fadina et al. (2019) and…

Mathematical Finance · Quantitative Finance 2024-06-11 Benedikt Geuchen , Katharina Oberpriller , Thorsten Schmidt