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We consider a stochastic volatility model where the dynamics of the volatility are given by a possibly infinite linear combination of the elements of the time extended signature of a Brownian motion. First, we show that the model is…

Pricing of Securities · Quantitative Finance 2025-06-03 Eduardo Abi Jaber , Louis-Amand Gérard

Stochastic exponentials are defined for semimartingales on stochastic intervals, and stochastic logarithms are defined for semimartingales, up to the first time the semimartingale hits zero continuously. In the case of (nonnegative) local…

Probability · Mathematics 2020-09-16 Martin Larsson , Johannes Ruf

In this paper we discuss existence and uniqueness for a one-dimensional time inhomogeneous stochastic differential equation directed by an $\mathbb{F}$-semimartingale $M$ and a finite cubic variation process $\xi$ which has the structure…

Probability · Mathematics 2007-05-23 Rosanna Coviello , Francesco Russo

The Heisenberg time-energy relation prevents determination of an atomic transition to better than the inverse of the measurement time. The relation generally applies to frequency estimation of a near-resonant field [1-3], since information…

Quantum Physics · Physics 2021-06-08 Liam P. McGuinness

In this paper, we present an overview of the recent developments of functional quantization of stochastic processes, with an emphasis on the quadratic case. Functional quantization is a way to approximate a process, viewed as a…

Probability · Mathematics 2013-04-03 Gilles Pagès

We introduce an efficient method for computing the Stekloff eigenvalues associated with the Helmholtz equation. In general, this eigenvalue problem requires solving the Helmholtz equation with Dirichlet and/or Neumann boundary condition…

Numerical Analysis · Mathematics 2017-11-17 Yangqingxiang Wu , Ludmil T Zikatanov

Let $(\mathcal{E},D(\mathcal{E}))$ be a quasi-regular semi-Dirichlet form and $(X_t)_{t\geq0}$ be the associated Markov process. For $u\in D(\mathcal{E})_{loc}$, denote $A_t^{[u]}:=\tilde{u}(X_{t})-\tilde{u}(X_{0})$ and…

Probability · Mathematics 2014-06-11 Chuan-Zhong Chen , Li Ma , Wei Sun

We study Fourier multipliers resulting from martingale transforms of general L\'evy processes.

Probability · Mathematics 2011-04-19 Rodrigo Bañuelos , Adam Bielaszewski , Krzysztof Bogdan

Recently, a new approach in the fine analysis of stochastic processes sample paths has been developed to predict the evolution of the local regularity under (pseudo-)differential operators. In this paper, we study the sample paths of…

Probability · Mathematics 2013-08-29 Paul Balança , Erick Herbin

We propose new concentration inequalities for self-normalized martingales. The main idea is to introduce a suitable weighted sum of the predictable quadratic variation and the total quadratic variation of the martingale. It offers much more…

Probability · Mathematics 2019-06-17 Bernard Bercu , Taieb Touati

Fourier transform of multivariate orthogonal polynomials on the unit ball are obtained. By using Parseval's identity, a new family of multivariate orthogonal functions are introduced. The results are expressed in terms of the continuous…

Classical Analysis and ODEs · Mathematics 2022-09-19 Esra Güldoğan Lekesiz , Rabia Aktaş , Iván Area

In this note, we present a version of Hoeffding's inequality in a continuous-time setting, where the data stream comes from a uniformly ergodic diffusion process. Similar to the well-studied case of Hoeffding's inequality for discrete-time…

Probability · Mathematics 2019-03-26 Michael C. H. Choi , Evelyn Li

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 article we present a Bernstein inequality for sums of random variables which are defined on a spatial lattice structure. The inequality can be used to derive concentration inequalities. It can be useful to obtain consistency…

Statistics Theory · Mathematics 2017-12-06 Eduardo Valenzuela-Domínguez , Johannes T. N. Krebs , Jürgen E. Franke

We consider stochastic versions of the Cauchy exponential functional equation and give a martingale characterization of the general solution.

Probability · Mathematics 2021-12-30 Beso Chikvinidze , Michael Mania , Revaz Tevzadze

Let $\mu$ be a probability measure on $\mathbb{R}$. We give conditions on the Fourier transform of its density for functionals of the form $H(a)=\int_{\mathbb{R}^n}h(\langle a,x\rangle)\mu^n(dx)$ to be Schur monotone. As applications, we…

Probability · Mathematics 2025-04-09 Andreas Malliaris

A vector-valued version of the Girsanov theorem is presented, for a scalar process with respect to a Banach-valued measure. Previously, a short discussion about the Birkhoff-type integration is outlined, as for example integration by…

Functional Analysis · Mathematics 2019-12-04 Domenico Candeloro , Anna Rita Sambucini

Matrix determinants play an important role in data analysis, in particular when Gaussian processes are involved. Due to currently exploding data volumes, linear operations - matrices - acting on the data are often not accessible directly…

Data Analysis, Statistics and Probability · Physics 2015-07-08 Sebastian Dorn , Torsten A. Enßlin

The aim of this paper is to prove an analogue of Baxter's inequality for fractional Brownian motion-type processes with Hurst index less than 1/2. This inequality is concerned with the norm estimate of the difference between finite- and…

Probability · Mathematics 2008-01-17 Akihiko Inoue , Yukio Kasahara , Punam Phartyal

We introduce a class of Markov chains, that contains the model of stochastic approximation by averaging and non-averaging. Using martingale approximation method, we establish various deviation inequalities for separately Lipschitz functions…

Probability · Mathematics 2022-09-16 Xiequan Fan , Pierre Alquier , Paul Doukhan
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