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In this paper we examine the asymptotic theory for U-statistics and V-statistics of discontinuous Ito semimartingales that are observed at high frequency. For different types of kernel functions we show laws of large numbers and associated…

Probability · Mathematics 2015-05-25 Mark Podolskij , Christian Schmidt , Mathias Vetter

We analyze the fluctuations of incomplete $U$-statistics over a triangular array of independent random variables. We give criteria for a Central Limit Theorem (CLT, for short) to hold in the sense that we prove that an appropriately scaled…

Probability · Mathematics 2020-03-24 Matthias Löwe , Sara Terveer

This paper presents some limit theorems for certain functionals of moving averages of semimartingales plus noise which are observed at high frequency. Our method generalizes the pre-averaging approach (see [Bernoulli 15 (2009) 634--658,…

Statistics Theory · Mathematics 2010-10-05 Jean Jacod , Mark Podolskij , Mathias Vetter

We study (asymmetric) $U$-statistics based on a stationary sequence of $m$-dependent variables; moreover, we consider constrained $U$-statistics, where the defining multiple sum only includes terms satisfying some restrictions on the gaps…

Probability · Mathematics 2022-03-10 Svante Janson

The estimation of local characteristics of Ito semimartingales has received a great deal of attention in both academia and industry over the past decades. In various papers limit theorems were derived for functionals of increments and…

Statistics Theory · Mathematics 2014-03-04 Moritz Duembgen , Mark Podolskij

We deduce in this paper the sufficient conditions for weak convergence of centered and normed deviation of the u-statistics with values in the space of the real valued continuous function defined on some compact metric space. We obtain also…

Statistics Theory · Mathematics 2016-08-12 E. Ostrovsky , L. Sirota

It is shown how the central limit theorem for U-statistics of spatial Poisson point processes can help to derive the central limit theorem for U-statistics of a Gibbs facet process from stochastic geometry. A full-dimensional submodel…

Probability · Mathematics 2016-08-03 Jakub Vecera , Viktor Benes

We investigate the almost sure asymptotic properties of vector martingale transforms. Assuming some appropriate regularity conditions both on the increasing process and on the moments of the martingale, we prove that normalized moments of…

Probability · Mathematics 2018-12-05 Bernard Bercu , Peggy Cénac , Guy Fayolle

This paper derives the asymptotic behavior of realized power variation of pure-jump It\^{o} semimartingales as the sampling frequency within a fixed interval increases to infinity. We prove convergence in probability and an associated…

Probability · Mathematics 2011-04-07 Viktor Todorov , George Tauchen

In this paper, we consider U-statistics whose data is a strictly stationary sequence which can be expressed as a functional of an i.i.d. one. We establish a strong law of large numbers, a bounded law of the iterated logarithms and a central…

Probability · Mathematics 2021-04-22 Davide Giraudo

We derive limit theorems for the empirical distribution function of "devolatilized" increments of an It\^{o} semimartingale observed at high frequencies. These "devolatilized" increments are formed by suitably rescaling and truncating the…

Probability · Mathematics 2014-07-03 Viktor Todorov , George Tauchen

We study the number of occurrences of any fixed vincular permutation pattern. We show that this statistics on uniform random permutations is asymptotically normal and describe the speed of convergence. To prove this central limit theorem,…

Combinatorics · Mathematics 2023-06-22 Lisa Hofer

We discuss in detail the asymptotic distribution of sample expectiles. First, we show uniform consistency under the assumption of a finite mean. In case of a finite second moment, we show that for expectiles other then the mean, only the…

Methodology · Statistics 2016-07-14 Hajo Holzmann , Bernhard Klar

We study asymptotic anytime-valid confidence sequences for degree-two U-statistics under continuous monitoring. In the nondegenerate case, Hoeffding's projection reduces the problem to a time-uniform central limit theory for the partial…

Statistics Theory · Mathematics 2026-05-19 Leheng Cai , Qirui Hu , Weijia Li

We establish a central limit theorem for the unnormalized linear statistic of the Gaussian Unitary Ensemble under optimal conditions: the linear statistics converges if and only if the expression for the limiting variance is finite.

Probability · Mathematics 2015-10-14 Phil Kopel

In this paper, we aim at estimating the quarticity of continuous It\^{o} semimartingales. Instead of using some classical estimators, we introduce a more intuitive one and establish a central limit theorem (CLT) for it, with a convergence…

Statistics Theory · Mathematics 2026-05-01 Yi Guo

For uniform random permutations conditioned to have no long cycles, we prove that the total number of cycles satisfies a central limit theorem. Under additional assumptions on the asymptotic behavior of the set of allowed cycle lengths, we…

Probability · Mathematics 2016-08-31 Volker Betz , Helge Schäfer

This paper is mainly concerned with asymptotic studies of weighted bootstrap for u- and v-statistics. We derive the consistency of the weighted bootstrap u- and v-statistics, based on i.i.d. and non i.i.d. observations, from some more…

Statistics Theory · Mathematics 2012-10-23 Miklos Csorgo , Masoud M. Nasari

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 consider sequences of symmetric $U$-statistics, not necessarily Hoeffding-degenerate, both in a one- and multi-dimensional setting, and prove quantitative central limit theorems (CLTs) based on the use of {\it contraction operators}. Our…

Probability · Mathematics 2021-04-01 Christian Döbler , Giovanni Peccati
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