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In this paper, we focus on the scaling-limit of the random potential $\beta$ associated with the Vertex Reinforced Jump Process (VRJP) on one-dimensional graphs. Moreover, we give a few applications of this scaling-limit. By considering a…

Probability · Mathematics 2023-08-03 V Rapenne , C Sabot

This paper is devoted to the nonparametric estimation of the jump rate and the cumulative rate for a general class of non-homogeneous marked renewal processes, defined on a separable metric space. In our framework, the estimation needs only…

Statistics Theory · Mathematics 2015-06-04 Romain Azaïs , François Dufour , Anne Gégout-Petit

The typical central limit theorems in high-frequency asymptotics for semimartingales are results on stable convergence to a mixed normal limit with an unknown conditional variance. Estimating this conditional variance usually is a hard…

Probability · Mathematics 2020-03-25 Mathias Vetter

We analyze a solution method for minimization problems over a space of $\mathbb{R}^d$-valued functions of bounded variation on an interval $I$. The presented method relies on piecewise constant iterates. In each iteration the algorithm…

Optimization and Control · Mathematics 2021-06-02 Philip Trautmann , Daniel Walter

Jump functions are the {most-studied} non-unimodal benchmark in the theory of randomized search heuristics, in particular, evolutionary algorithms (EAs). They have significantly improved our understanding of how EAs escape from local…

Neural and Evolutionary Computing · Computer Science 2024-10-08 Henry Bambury , Antoine Bultel , Benjamin Doerr

The problem of drift estimation for the solution $X$ of a stochastic differential equation with L\'evy-type jumps is considered under discrete high-frequency observations with a growing observation window. An efficient and asymptotically…

Statistics Theory · Mathematics 2016-03-18 Arnaud Gloter , Dasha Loukianova , Hilmar Mai

Given a discrete time sample $X_1,... X_n$ from a L\'evy process $X=(X_t)_{t\geq 0}$ of a finite jump activity, we study the problem of nonparametric estimation of the characteristic triplet $(\gamma,\sigma^2,\rho)$ corresponding to the…

Statistics Theory · Mathematics 2018-04-17 Shota Gugushvili

Volatility estimation is a central problem in financial econometrics, but becomes particularly challenging when jump activity is high, a phenomenon observed empirically in highly traded financial securities. In this paper, we revisit the…

Econometrics · Economics 2026-05-13 B. Cooper Boniece , José E. Figueroa-López , Tianwei Zhou

In this paper, we study the nonparametric estimation of the density $f_\Delta$ of an increment of a L\'evy process $X$ based on $n$ observations with a sampling rate $\Delta$. The class of L\'evy processes considered is broad, including…

Statistics Theory · Mathematics 2024-11-04 Céline Duval , Taher Jalal , Ester Mariucci

We propose a new estimation scheme for estimation of the volatility parameters of a semimartingale with jumps based on a jump-detection filter. Our filter uses all of data to analyze the relative size of increments and to discriminate jumps…

Methodology · Statistics 2021-02-16 Haruhiko Inatsugu , Nakahiro Yoshida

We define a generalized index of jump activity, propose estimators of that index for a discretely sampled process and derive the estimators' properties. These estimators are applicable despite the presence of Brownian volatility in the…

Statistics Theory · Mathematics 2009-08-24 Yacine Aït-Sahalia , Jean Jacod

For a semimartingale with jumps, we propose a new estimation method for integrated volatility, i.e., the quadratic variation of the continuous martingale part, based on the global jump filter proposed by Inatsugu and Yoshida [8]. To decide…

Statistics Theory · Mathematics 2021-02-16 Haruhiko Inatsugu , Nakahiro Yoshida

In a high-frequency context, we investigate the efficient estimation of scaling and jump activity parameters for a stochastic differential equation driven by a L{\'e}vy process with both diffusion component and pure-jump component. We first…

Probability · Mathematics 2025-09-08 Elise Bayraktar , Emmanuelle Clément

An efficient estimator is constructed for the quadratic covariation or integrated co-volatility matrix of a multivariate continuous martingale based on noisy and nonsynchronous observations under high-frequency asymptotics. Our approach…

Statistics Theory · Mathematics 2014-07-02 Markus Bibinger , Nikolaus Hautsch , Peter Malec , Markus Reiß

Piecewise-deterministic Markov processes (PDMPs) offer a powerful stochastic modeling framework that combines deterministic trajectories with random perturbations at random times. Estimating their local characteristics (particularly the…

Methodology · Statistics 2025-12-29 Romain Azaïs , Solune Denis

In this paper, we consider a one-dimensional diffusion process with jumps driven by a Hawkes process. We are interested in the estimations of the volatility function and of the jump function from discrete high-frequency observations in a…

Statistics Theory · Mathematics 2022-04-28 Chiara Amorino , Charlotte Dion , Arnaud Gloter , Sarah Lemler

We consider the problem of adaptive estimation of the regression function in a framework where we replace ergodicity assumptions (such as independence or mixing) by another structural assumption on the model. Namely, we propose adaptive…

Statistics Theory · Mathematics 2010-11-03 Sylvain Delattre , Stéphane Gaïffas

We consider a univariate semimartingale model for (the logarithm of) an asset price, containing jumps having possibly infinite activity (IA). The nonparametric threshold estimator of the integrated variance IV proposed in Mancini 2009 is…

Statistical Finance · Quantitative Finance 2017-08-16 José E. Figueroa-López , Cecilia Mancini

We consider a pure jump process $\{X_t\}_{t\ge 0}$ with values in a finite state space $S= \{1, \ldots, d\}$ for which the jump rates at time instant $t$ depend on the occupation measure $L_t \doteq t^{-1} \int_0^t \delta_{X_s}\,ds$. Such…

Probability · Mathematics 2025-10-17 Amarjit Budhiraja , Francesco Coghi

The coefficient function of the leading differential operator is estimated from observations of a linear stochastic partial differential equation (SPDE). The estimation is based on continuous time observations which are localised in space.…

Statistics Theory · Mathematics 2021-03-30 Randolf Altmeyer , Markus Reiß