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Stochastic approximation is a powerful class of algorithms with celebrated success. However, a large body of previous analysis focuses on stochastic approximations driven by contractive operators, which is not applicable in some important…

Machine Learning · Computer Science 2025-11-21 Ethan Blaser , Shangtong Zhang

For symmetric L\'evy processes, if the local times exist, the Tanaka formula has already constructed via the techniques in the potential theory by Salminen and Yor (2007). In this paper, we study the Tanaka formula for arbitrary strictly…

Probability · Mathematics 2017-02-03 Hiroshi Tsukada

The use of machine learning methods for predictive purposes has increased dramatically over the past two decades, but uncertainty quantification for predictive comparisons remains elusive. This paper addresses this gap by extending the…

Econometrics · Economics 2025-05-09 Juan Carlos Escanciano , Ricardo Parra

We obtain asymptotic expansions for the large deviation principle (LDP) for continuous time stochastic processes with weakly dependent increments. As a key example, we show that additive functionals of solutions of stochastic differential…

Probability · Mathematics 2021-04-06 Kasun Fernando , Pratima Hebbar

We extend the It\^o-Wentzell formula for the evolution along a continuous semimartingale of a time-dependent stochastic field driven by a continuous semimartingale to tensor field-valued stochastic processes on manifolds. More concretely,…

Probability · Mathematics 2023-11-09 Aythami Bethencourt de León , So Takao

This article studies the solutions of time-dependent differential inclusions which is motivated by their utility in the modeling of certain physical systems. The differential inclusion is described by a time-dependent set-valued mapping…

Optimization and Control · Mathematics 2021-07-05 Kanat Camlibel , Luigi Iannelli , Aneel Tanwani

We show that, under certain smoothness conditions, a Brownian martingale, when evaluated at a fixed time, can be represented via an exponential formula at a later time. The time-dependent generator of this exponential operator only depends…

Probability · Mathematics 2015-10-27 Sixian Jin , Qidi Peng , Henry Schellhorn

In this paper, we introduce a targeted exploration strategy for the non-asymptotic, finite-time case. The proposed strategy is applicable to uncertain linear time-invariant systems subject to sub-Gaussian disturbances. As the main result,…

Systems and Control · Electrical Eng. & Systems 2026-04-17 Janani Venkatasubramanian , Johannes Köhler , Frank Allgöwer

We consider the identification problem of a noncausal Ito process from its stochastic Fourier coefficients with respect to the complete system of trigonometric functions. Here, a noncausal Ito process is the extension of Ito process whose…

Probability · Mathematics 2016-04-01 Shigeyoshi Ogawa , Hideaki Uemura

By application of the theory for second-order linear differential equations with two turning points developed in [Olver F.W.J., Philos. Trans. Roy. Soc. London Ser. A 278 (1975), 137-174], uniform asymptotic approximations are obtained in…

Classical Analysis and ODEs · Mathematics 2015-11-25 Karen Ogilvie , Adri B. Olde Daalhuis

We consider a stochastic volatility model with L\'evy jumps for a log-return process $Z=(Z_{t})_{t\geq 0}$ of the form $Z=U+X$, where $U=(U_{t})_{t\geq 0}$ is a classical stochastic volatility process and $X=(X_{t})_{t\geq 0}$ is an…

Pricing of Securities · Quantitative Finance 2012-02-23 J. E. Figueroa-López , R. Gong , C. Houdré

Given a sequence of resistance forms that converges with respect to the Gromov-Hausdorff-vague topology and satisfies a uniform volume doubling condition, we show the convergence of corresponding Brownian motions and local times. As a…

Probability · Mathematics 2016-09-08 D. A. Croydon , B. M. Hambly , T. Kumagai

In this paper, we derive new asymptotic expansions for the solutions of higher order elliptic equations in the presence of small inclusions. As a byproduct, we derive a topological derivative based algorithm for the reconstruction of…

Analysis of PDEs · Mathematics 2020-01-01 Andrea Aspri , Elena Beretta , Otmar Scherzer , Monika Muszkieta

In this paper we study the {\it pathwise stochastic Taylor expansion}, in the sense of our previous work \cite{Buckdahn_Ma_02}, for a class of It\^o-type random fields in which the diffusion part is allowed to contain both the random field…

Probability · Mathematics 2010-08-20 Rainer Buckdahn , Ingo Bulla , Jin Ma

We consider integer-valued random walks with independent but not identically distributed increments, and extend to this context several classical estimates, including a local limit theorem, precise small-ball estimates (both conditional on…

Probability · Mathematics 2025-11-13 Sébastien Ott , Yvan Velenik

This paper focuses on the task of detecting local episodes involving violation of the standard It\^o semimartingale assumption for financial asset prices in real time that might induce arbitrage opportunities. Our proposed detectors,…

Econometrics · Economics 2023-07-21 Torben G. Andersen , Viktor Todorov , Bo Zhou

The article is devoted to the expansion of iterated Ito stochastic integrals of second multiplicity based on expansion of the Brownian motion (standard Wiener process) using complete orthonormal systems of functions in the space $L_2([t,…

Probability · Mathematics 2026-02-17 Dmitriy F. Kuznetsov

In this work, we generalise the stochastic local time space integration introduced in \cite{Ei00} to the case of Brownian sheet. %We develop a stochastic local time-space calculus with respect to the Brownian sheet. This allows us to prove…

Probability · Mathematics 2023-08-25 Antoine-Marie Bogso , Moustapha Dieye , Olivier Menoukeu Pamen

We study the asymptotic properties of an estimator of Hurst parameter of a stochastic differential equation driven by a fractional Brownian motion with $H > 1/2$. Utilizing the theory of asymptotic expansion of Skorohod integrals introduced…

Probability · Mathematics 2024-07-03 Hayate Yamagishi

The literature on time series of functional data has focused on processes of which the probabilistic law is either constant over time or constant up to its second-order structure. Especially for long stretches of data it is desirable to be…

Methodology · Statistics 2020-07-21 Anne van Delft , Michael Eichler