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Markov jump processes (MJPs) are used to model a wide range of phenomena from disease progression to RNA path folding. However, maximum likelihood estimation of parametric models leads to degenerate trajectories and inferential performance…

Machine Learning · Statistics 2015-06-08 Jonathan H. Huggins , Karthik Narasimhan , Ardavan Saeedi , Vikash K. Mansinghka

We derive a nonparametric test for constant beta over a fixed time interval from high-frequency observations of a bivariate \Ito semimartingale. Beta is defined as the ratio of the spot continuous covariation between an asset and a risk…

Statistics Theory · Mathematics 2015-02-20 Markus Reiß , Viktor Todorov , George Tauchen

In this paper, local linear estimators are adapted for the unknown infinitesimal coefficients associated with continuous-time asset return model with jumps, which can correct the bias automatically due to their simple bias representation.…

Statistics Theory · Mathematics 2018-02-15 Yuping Song , Ying Chen , Zhouwei Wang

We consider noisy non-synchronous discrete observations of a continuous semimartingale with random volatility. Functional stable central limit theorems are established under high-frequency asymptotics in three setups: one-dimensional for…

Statistics Theory · Mathematics 2015-07-28 Randolf Altmeyer , Markus Bibinger

This paper proposes a new integrated variance estimator based on order statistics within the framework of jump-diffusion models. Its ability to disentangle the integrated variance from the total process quadratic variation is confirmed by…

Risk Management · Quantitative Finance 2018-03-23 Luca Spadafora , Francesca Sivero , Nicola Picchiotti

This paper investigates almost sure exponential stabilization of continuous-time Markov jump linear systems (MJLSs) under communication data-rate constraints by introducing sampling and quantization into the feedback control. Different from…

Dynamical Systems · Mathematics 2021-10-29 Jingyi Wang , Jianwen Feng , Chen Xu , Xiaoqun Wu , Jinhu Lü

We propose statistical tests to discriminate between the finite and infinite activity of jumps in a semimartingale discretely observed at high frequency. The two statistics allow for a symmetric treatment of the problem: we can either take…

Statistics Theory · Mathematics 2012-11-26 Yacine Aït-Sahalia , Jean Jacod

The paper considers the problem of robust estimating a periodic function in a continuous time regression model with dependent disturbances given by a general square integrable semimartingale with unknown distribution. An example of such a…

Statistics Theory · Mathematics 2010-10-20 Victor Konev , Serguei Pergamenchtchikov

We investigate a semiparametric regression model where one gets noisy non linear non invertible functions of the observations. We focus on the application to bearings-only tracking. We first investigate the least squares estimator and prove…

Statistics Theory · Mathematics 2008-12-17 Elisabeth Gassiat , Benoit Landelle

In this paper, robust nonparametric estimators, instead of local linear estimators, are adapted for infinitesimal coefficients associated with integrated jump-diffusion models to avoid the impact of outliers on accuracy. Furthermore,…

Statistics Theory · Mathematics 2018-06-26 Yuping Song , Hanchao Wang

In this paper we study a family of nonlinear (conditional) expectations that can be understood as a semimartingale with uncertain local characteristics. Here, the differential characteristics are prescribed by a time and path-dependent…

Probability · Mathematics 2023-11-07 David Criens , Lars Niemann

This paper is concerned with asymptotic behavior of a variety of functionals of increments of continuous semimartingales. Sampling times are assumed to follow a rather general discretization scheme. If an underlying semimartingale is…

Probability · Mathematics 2024-10-04 Michael Levine , Xiaoguang Wang , Jian Frank Zou

We consider the moderate deviations behaviors for two (co-) volatility estima-tors: generalised bipower variation, Hayashi-Yoshida estimator. The results are obtained by using a new result about the moderate deviations principle for…

Probability · Mathematics 2017-02-06 Hacène Djellout , Arnaud Guillin , Hui Jiang , Yacouba Samoura

A new integral with respect to an integer-valued random measure is introduced. In contrast to the finite variation integral ubiquitous in semimartingale theory (Jacod and Shiryaev, 2003, II.1.5), the new integral is closed under stochastic…

Probability · Mathematics 2021-08-26 Aleš Černý , Johannes Ruf

In this paper, we first investigate the estimation of the empirical joint Laplace transform of volatilities of two semi-martingales within a fixed time interval [0, T] by using overlapped increments of high-frequency data. The proposed…

Statistics Theory · Mathematics 2025-03-05 XinWei Feng , Yu Jiang , Zhi Liu , Zhe Meng

We study the nonparametric calibration of exponential L\'{e}vy models with infinite jump activity. In particular our analysis applies to self-decomposable processes whose jump density can be characterized by the $k$-function, which is…

Statistics Theory · Mathematics 2014-02-05 Mathias Trabs

In this paper, we propose a new jump robust quantile-based realised variance measure of ex-post return variation that can be computed using potentially noisy data. The estimator is consistent for the integrated variance and we present…

Econometrics · Economics 2026-01-21 Kim Christensen , Roel Oomen , Mark Podolskij

We derive a nonparametric higher-order asymptotic expansion for small-time changes of conditional characteristic functions of It\^o semimartingale increments. The asymptotics setup is of joint type: both the length of the time interval of…

Statistical Finance · Quantitative Finance 2025-02-12 Carsten H. Chong , Viktor Todorov

We study the estimation of leverage effect and volatility of volatility by using high-frequency data with the presence of jumps. We first construct spot volatility estimator by using the empirical characteristic function of the…

Methodology · Statistics 2026-03-03 Qiang Liu , Zhi Liu , Wang Zhou

We develop an asymptotic theory for the jump robust measurement of covariations in the context of stochastic evolution equation in infinite dimensions. Namely, we identify scaling limits for realized covariations of solution processes with…

Methodology · Statistics 2025-09-09 Dennis Schroers