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We study representations of a random variable $\xi$ as an integral of an adapted process with respect to the Lebesgue measure. The existence of such representations in two different regularity classes is characterized in terms of the…

Probability · Mathematics 2023-08-08 Sara Biagini , Gordan Zitkovic

Representations of branching Markov processes and their measure-valued limits in terms of countable systems of particles are constructed for models with spatially varying birth and death rates. Each particle has a location and a "level,"…

Probability · Mathematics 2011-04-11 Thomas G. Kurtz , Eliane R. Rodrigues

In this paper we study splittings of a Poisson point process which are equivariant under a conservative transformation. We show that, if the Cartesian powers of this transformation are all ergodic, the only ergodic splitting is the obvious…

Probability · Mathematics 2018-11-21 Elise Janvresse , Emmanuel Roy , Thierry De La Rue

A scaling on some space is a measurable action of the group of positive real numbers. A measure on a measurable space equipped with a scaling is said to be $\alpha$-homogeneous for some nonzero real number $\alpha$ if the mass of any…

Probability · Mathematics 2017-08-15 Steven N. Evans , Ilya Molchanov

Introduced is the notion of minimality for spectral representations of sum- and max-infinitely divisible processes and it is shown that the minimal spectral representation on a Borel space exists and is unique. This fact is used to show…

Probability · Mathematics 2016-01-18 Zakhar Kabluchko , Stilian Stoev

We consider some versions and generalizations of an approach to the expansion of iterated Ito stochastic integrals of arbitrary multiplicity $k$ $(k\in\mathbb{N})$ based on generalized multiple Fourier series. Expansions of iterated…

Probability · Mathematics 2023-08-01 Dmitriy F. Kuznetsov

Let $\eta$ be a Poisson random measure (defined on some Polish space), and let $F(\eta)$ be a square-integrable functional of $\eta$. In this paper we define and study a new notion of {\it spectral point process} associated with $F(\eta)$,…

Probability · Mathematics 2024-07-19 Chinmoy Bhattacharjee , Giovanni Peccati , D. Yogeshwaran

Sets of orthogonal martingales are importants because they can be used as stochastic integrators in a kind of chaotic representation property, see [20]. In this paper, we revisited the problem studied by W. Schoutens in [21], investigating…

Probability · Mathematics 2013-11-19 Edmundo J. Huertas , Nuria Torrado , Fabrizio Leisen

We study the $\beta$ analogue of the nonintersecting Poisson random walks. We derive a stochastic differential equation of the Stieltjes transform of the empirical measure process, which can be viewed as a dynamical version of the…

Probability · Mathematics 2021-03-02 Jiaoyang Huang

Given a process with independent increments $X$ (not necessarily a martingale) and a large class of square integrable r.v. $H=f(X_T)$, $f$ being the Fourier transform of a finite measure $\mu$, we provide explicit Kunita-Watanabe and…

Probability · Mathematics 2012-02-06 Stéphane Goutte , Nadia Oudjane , Francesco Russo

In this work, we introduce a Monte Carlo method for the dynamic hedging of general European-type contingent claims in a multidimensional Brownian arbitrage-free market. Based on bounded variation martingale approximations for…

Pricing of Securities · Quantitative Finance 2013-08-20 Dorival Leão , Alberto Ohashi , Vinicius Siqueira

We give sufficient criteria for the Dol\'eans-Dade exponential of a stochastic integral with respect to a counting process local martingale to be a true martingale. The criteria are adapted particularly to the case of counting processes and…

Probability · Mathematics 2015-09-09 Alexander Sokol , Niels Richard Hansen

Using a suitable change of probability measure, we obtain a novel Poisson series representation for the arbitrage- free price process of vulnerable contingent claims in a regime-switching market driven by an underlying continuous- time…

Computational Finance · Quantitative Finance 2017-01-09 Agostino Capponi , Jose Figueroa-Lopez , Jeffrey Nisen

The classical representation of random variables as the Ito integral of nonanticipative integrands is extended to include Banach space valued random variables on an abstract Wiener space equipped with a filtration induced by a resolution of…

Probability · Mathematics 2008-03-16 E. Mayer-Wolf , M. Zakai

We introduce a new concept of dissipative measure-valued martingale solutions to the stochastic compressible Euler equations. These solutions are weak in the probabilistic sense i.e., the probability space and the driving Wiener process are…

Analysis of PDEs · Mathematics 2020-12-15 Martina Hofmanova , Ujjwal Koley , Utsab Sarkar

In this paper Clark-Ocone representation for solution to measure-valued equation with interaction is studied. It is proven that the integrand is absolutely continuous with respect to Lebesgue measure.

Probability · Mathematics 2021-03-09 Jasmina Đorđević , Andrey Dorogovtsev

We present a machine learning model for the analysis of randomly generated discrete signals, modeled as the points of an inhomogeneous, compound Poisson point process. Like the wavelet scattering transform introduced by Mallat, our…

Statistics Theory · Mathematics 2021-10-12 Michael Perlmutter , Jieqian He , Matthew Hirn

We study Wiener-type covering lemmas, Hardy-Littlewood-type maximal functions, and convergence theorems on metric spacs. Later we specialize down to a result for the Poisson integral. We show that, in a suitably general setting, these three…

Analysis of PDEs · Mathematics 2010-10-08 Steven G. Krantz

In this paper, the weak convergence of additive functionals of processes with locally independent increments and with Markov switching in the scheme of Poisson approximation is proved. For the relative compactness, a method proposed by R.…

Probability · Mathematics 2009-10-20 V. S. Koroliuk , N. Limnios , I. V. Samoilenko

We observe $n$ inhomogeneous Poisson processes with covariates and aim at estimating their intensities. We assume that the intensity of each Poisson process is of the form $s (\cdot, x)$ where $x$ is the covariate and where $s$ is an…

Statistics Theory · Mathematics 2013-06-14 Mathieu Sart