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We develop a stochastic integration theory for predictable integrands with respect to a L\'evy basis. Our approach is based on decoupling inequalities for tangent sequences and reduces the construction of the stochastic integral essentially…

Probability · Mathematics 2026-05-18 Markus Riedle

Stochastic integrals are defined with respect to a collection $P = (P_i; \, i \in I)$ of continuous semimartingales, imposing no assumptions on the index set $I$ and the subspace of $\mathbb{R}^I$ where $P$ takes values. The integrals are…

Probability · Mathematics 2019-08-20 Constantinos Kardaras

One problem of wide interest involves estimating expected crossing-times. Several tools have been developed to solve this problem beginning with the works of Wald and the theory of sequential analysis. An extension of his approach is…

Methodology · Statistics 2015-06-17 Mark Brown , Victor de la Pena , Tony Sit

The normalised partial sums of values of a nonnegative multiplicative function over divisors with appropriately restricted sizes of a random permutation from the symmetric group define trajectories of a stochastic process. We prove a…

Probability · Mathematics 2026-01-14 Eugenijus Manstavičius

When the limiting compensator of a sequence of martingales is continuous, we obtain a weak convergence theorem for the martingales; the limiting process can be written as a Brownian motion evaluated at the compensator and we find sufficient…

Probability · Mathematics 2024-01-22 Bruno Rémillard , Jean Vaillancourt

Parametric and nonparametric inference for stochastic processes driven by a fractional Brownian motion were investigated in Mishura (2008) and Prakasa Rao(2010) among others. Similar problems for processes driven by an infinite dimensional…

Probability · Mathematics 2021-03-10 B. L. S. Prakasa Rao

We consider shot-noise processes with an impulse response written in terms of the logarithm of the ratio between current and event time (instead of the usual absolute time difference). We study its finite-time properties as well as its weak…

Probability · Mathematics 2026-05-05 Luisa Beghin , Lorenzo Cristofaro , Enrico Scalas

This article focuses on a system of sticky Brownian motions, also known as Howitt-Warren martingale problem, and correlated Brownian motions and shows that infinite-dimensional orthogonal polynomials intertwine the dynamics of infinitely…

Probability · Mathematics 2024-02-12 Stefan Wagner

In this paper an arbitrage strategy is constructed for the modified Black-Scholes model driven by fractional Brownian motion or by a time changed fractional Brownian motion, when the volatility is stochastic. This latter property allows the…

Information Theory · Computer Science 2007-07-13 Erhan Bayraktar , H. Vincent Poor

In this paper, we prove maximal inequalities and study the functional central limit theorem for the partial sums of linear processes generated by dependent innovations. Due to the general weights, these processes can exhibit long-range…

Statistics Theory · Mathematics 2011-03-21 Jérôme Dedecker , Florence Merlevède , Magda Peligrad

The rate of strong convergence is investigated for an approximation scheme for a class of stochastic differential equations driven by a time-changed Brownian motion, where the random time changes $(E_t)_{t\ge 0}$ considered include the…

Probability · Mathematics 2020-03-02 Sixian Jin , Kei Kobayashi

We introduce a canonical method for transforming a discrete sequential data set into an associated rough path made up of lead-lag increments. In particular, by sampling a $d$-dimensional continuous semimartingale $X:[0,1] \rightarrow…

Probability · Mathematics 2016-08-25 Guy Flint , Ben Hambly , Terry Lyons

When analyzing probabilistic computations, a powerful approach is to first find a martingale---an expression on the program variables whose expectation remains invariant---and then apply the optional stopping theorem in order to infer…

Programming Languages · Computer Science 2018-03-16 Gilles Barthe , Thomas Espitau , Luis María Ferrer Fioriti , Justin Hsu

The paper studies stochastic integration with respect to Gaussian processes and fields. It is more convenient to work with a field than a process: by definition, a field is a collection of stochastic integrals for a class of deterministic…

Probability · Mathematics 2007-10-15 S. V. Lototsky , K. Stemmann

In this paper, martingales related to simple random walks and their maximum process are investigated. First, a sufficient condition under which a function with three arguments, time, the random walk, and its maximum process becomes a…

Probability · Mathematics 2022-11-11 Takahiko Fujita , Shotaro Yagishita , Naohiro Yoshida

Let $B$ be a fractional Brownian motion with Hurst parameter $H=1/6$. It is known that the symmetric Stratonovich-style Riemann sums for $\int g(B(s))\,dB(s)$ do not, in general, converge in probability. We show, however, that they do…

Probability · Mathematics 2010-06-23 Ivan Nourdin , Anthony Réveillac , Jason Swanson

We develop a class of pathwise inequalities of the form $H(B_t)\ge M_t+F(L_t)$, where $B_t$ is Brownian motion, $L_t$ its local time at zero and $M_t$ a local martingale. The concrete nature of the representation makes the inequality useful…

Probability · Mathematics 2008-12-02 A. M. G. Cox , David Hobson , Jan Obłój

In this article we introduce cylindrical fractional Brownian motions in Banach spaces and develop the related stochastic integration theory. Here a cylindrical fractional Brownian motion is understood in the classical framework of…

Probability · Mathematics 2015-11-19 Elena Issoglio , Markus Riedle

For a series of Markov processes we prove stochastic duality relations with duality functions given by orthogonal polynomials. This means that expectations with respect to the original process (which evolves the variable of the orthogonal…

Probability · Mathematics 2017-02-01 Chiara Franceschini , Cristian Giardinà

This paper contributes to the study of relative martingales. Specifically, for a closed random set $H$, they are processes null on $H$ which decompose as $M=m+v$, where $m$ is a c\`adl\`ag uniformly integrable martingale and, $v$ is a…

Probability · Mathematics 2022-10-04 Fulgence Eyi Obiang , Paule Joyce Mbenangoya , Ibrahima Faye , Octave Moutsinga