Mark Podolskij

Mark Podolskij

Université du Luxembourg

H-index: 30

Europe-Luxembourg

About Mark Podolskij

Mark Podolskij, With an exceptional h-index of 30 and a recent h-index of 20 (since 2020), a distinguished researcher at Université du Luxembourg,

His recent articles reflect a diverse array of research interests and contributions to the field:

On nonparametric estimation of the interaction function in particle system models

Optimal estimation of the local time and the occupation time measure for an α-stable Lévy process

Book review: How to Cheat with Statistics–and Get Away with It, by Gunter Meissner, World Scientific (2022), Hardback. ISBN 978-9811252488

Limit theorems for general functionals of Brownian local times

Quantitative and stable limits of high-frequency statistics of L\'evy processes: a Stein's method approach

Estimation of mixed fractional stable processes using high-frequency data

Semiparametric estimation of McKean–Vlasov SDEs

Parameter estimation of discretely observed interacting particle systems

Mark Podolskij Information

University

Position

Professor of Probability and Statistics

Citations(all)

4472

Citations(since 2020)

1628

Cited By

3623

hIndex(all)

30

hIndex(since 2020)

20

i10Index(all)

42

i10Index(since 2020)

36

Email

University Profile Page

Université du Luxembourg

Google Scholar

View Google Scholar Profile

Top articles of Mark Podolskij

Title

Journal

Author(s)

Publication Date

On nonparametric estimation of the interaction function in particle system models

arXiv preprint arXiv:2402.14419

Denis Belomestny

Mark Podolskij

Shi-Yuan Zhou

2024/2/22

Optimal estimation of the local time and the occupation time measure for an α-stable Lévy process

Modern Stochastics: Theory and Applications

Chiara Amorino

Arturo Jaramillo

Mark Podolskij

2024/2/6

Book review: How to Cheat with Statistics–and Get Away with It, by Gunter Meissner, World Scientific (2022), Hardback. ISBN 978-9811252488

Mark Podolskij

2024/1/2

Limit theorems for general functionals of Brownian local times

arXiv preprint arXiv:2311.01251

Simon Campese

Nicolas Lengert

Mark Podolskij

2023/11/2

Quantitative and stable limits of high-frequency statistics of L\'evy processes: a Stein's method approach

arXiv preprint arXiv:2302.05885

Chiara Amorino

Arturo Jaramillo

Mark Podolskij

2023/2/12

Estimation of mixed fractional stable processes using high-frequency data

The Annals of Statistics

Fabian Mies

Mark Podolskij

2023/10

Semiparametric estimation of McKean–Vlasov SDEs

Annales de l'Institut Henri Poincare (B) Probabilites et statistiques

Denis Belomestny

Vytautė Pilipauskaitė

Mark Podolskij

2023/2

Parameter estimation of discretely observed interacting particle systems

Stochastic Processes and their Applications

Chiara Amorino

Akram Heidari

Vytautė Pilipauskaitė

Mark Podolskij

2023/9/1

High-dimensional estimation of quadratic variation based on penalized realized variance

Statistical Inference for Stochastic Processes

Kim Christensen

Mikkel Slot Nielsen

Mark Podolskij

2023/7

Asymptotic theory for quadratic variation of harmonizable fractional stable processes

arXiv preprint arXiv:2302.14034

Andreas Basse-O'Connor

Mark Podolskij

2023/2/27

Optimal estimation of the supremum and occupation times of a self-similar Lévy process

Electronic Journal of Statistics

Jevgenijs Ivanovs

Mark Podolskij

2022

Optimal estimation of local time and occupation time measure for an↵-stable Lévy process

Chiara Amorino

Arturo Jaramillo

Mark Podolskij

2022/10/14

On Lasso estimator for the drift function in diffusion models

arXiv preprint arXiv:2209.05974

Gabriela Ciolek

Dmytro Marushkevych

Mark Podolskij

2022/9/13

Multidimensional parameter estimation of heavy‐tailed moving averages

Scandinavian Journal of Statistics

Mathias Mørck Ljungdahl

Mark Podolskij

2022/6

On estimation of quadratic variation for multivariate pure jump semimartingales

Stochastic Processes and their Applications

Johannes Heiny

Mark Podolskij

2021/8/1

Power variations for fractional type infinitely divisible random fields

Andreas Basse-O’Connor

Vytautė Pilipauskaitė

Mark Podolskij

2021

Local asymptotic self-similarity for heavy tailed harmonizable fractional Lévy motions

ESAIM: Probability and Statistics

Andreas Basse-O’Connor

Thorbjørn Grønbæk

Mark Podolskij

2021

Multi-dimensional parameter estimation of heavy-tailed moving averages

arXiv e-prints

Mathias Mørck Ljungdahl

Mark Podolskij

2020/7

On Dantzig and Lasso estimators of the drift in a high dimensional Ornstein-Uhlenbeck model

Gabriela Ciołek

Dmytro Marushkevych

Mark Podolskij

2020/1/1

A minimal contrast estimator for the linear fractional stable motion

Statistical Inference for Stochastic Processes

Mathias Mørck Ljungdahl

Mark Podolskij

2020/7

See List of Professors in Mark Podolskij University(Université du Luxembourg)

Co-Authors

H-index: 36
Per Mykland

Per Mykland

University of Chicago

H-index: 19
Jose Manuel Corcuera

Jose Manuel Corcuera

Universidad de Barcelona

H-index: 18
Mathias Vetter

Mathias Vetter

Christian-Albrechts-Universität zu Kiel

H-index: 13
Kim Christensen

Kim Christensen

Aarhus Universitet

H-index: 12
Andreas Basse-O'Connor

Andreas Basse-O'Connor

Aarhus Universitet

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