World's Best Scientists 2026 revealed!

Overview

Mark Podolskij is affiliated with the University of Luxembourg in Luxembourg. Their research primarily spans the fields of Economics, Econometrics and Finance, with a secondary focus on Mathematics. Their work intersects several subfields including Finance, Statistics and Probability, Mathematical Physics, Management Science and Operations Research, and Economics and Econometrics.

The main topics covered in their research explore areas such as stochastic processes and financial applications, financial risk and volatility modeling, statistical methods and inference, stochastic processes and statistical mechanics, probability and risk models, Markov chains and Monte Carlo methods, and complex systems and time series analysis.

Mark Podolskij has published numerous papers in a range of academic journals and publication venues. Frequent venues include arXiv (Cornell University), Electronic Journal of Statistics, Stochastic Processes and their Applications, Open Repository and Bibliography (University of Luxembourg), and Electronic Journal of Probability.

Examples of recent publications include:

  • "Semiparametric estimation of McKean-Vlasov SDEs" (2023), Annales de l Institut Henri Poincaré Probabilités et Statistiques
  • "Parameter estimation of discretely observed interacting particle systems" (2023), Stochastic Processes and their Applications
  • "Polynomial rates via deconvolution for nonparametric estimation in McKean-Vlasov SDEs" (2024), Probability Theory and Related Fields
  • "On Dantzig and Lasso estimators of the drift in a high dimensional Ornstein-Uhlenbeck model" (2020), Electronic Journal of Statistics
  • "A Berry-Esseén theorem for partial sums of functionals of heavy-tailed moving averages" (2020), Electronic Journal of Probability

Collaboration is a notable aspect of their research career, with frequent coauthors including Chiara Amorino, Vytautė Pilipauskaitė, Dmytro Marushkevych, Akram Heidari, and Gabriela Ciołek.

Best Publications

  • Microstructure Noise in the Continuous Case: The Pre-Averaging Approach ∗

    Jean Jacod;Yingying Li;Per A. Mykland;Mark Podolskij

  • Realized range-based estimation of integrated variance

    Kim Christensen;Mark Podolskij

  • Estimation of volatility functionals in the simultaneous presence of microstructure noise and jumps

    Mark Podolskij;Mathias Vetter

  • Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data

    Kim Christensen;Silja Kinnebrock;Mark Podolskij;Mark Podolskij

  • Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps

    Mark Podolskij;Mathias Vetter;Margit Sommer

  • A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales

    Ole E. Barndorff-Nielsen;Svend Erik Graversen;Jean Jacod;Mark Podolskij

  • Fact or friction: Jumps at ultra high frequency☆

    Kim Christensen;Roel C.A. Oomen;Roel C.A. Oomen;Mark Podolskij

  • Realised quantile-based estimation of the integrated variance

    Kim Christensen;Roel Oomen;Roel Oomen;Mark Podolskij;Mark Podolskij

  • A central limit theorem for realised power and bipower variations of continuous semimartingales

    Ole E. Barndorff–Nielsen;Svend Erik Graversen;Jean Jacod;Mark Podolskij

  • Bipower-type estimation in a noisy diffusion setting☆

    Mark Podolskij;Mathias Vetter

  • Pre-averaging based estimation of quadratic variation in the presence of noise and jumps: Theory, implementation, and empirical evidence

    Nikolaus Hautsch;Mark Podolskij

  • Limit theorems for moving averages of discretized processes plus noise

    Jean Jacod;Mark Podolskij;Mathias Vetter

  • Power variation for Gaussian processes with stationary increments

    Ole E. Barndorff-Nielsen;José Manuel Corcuera;Mark Podolskij

  • On covariation estimation for multivariate continuous Itô semimartingales with noise in non-synchronous observation schemes

    Kim Christensen;Mark Podolskij;Mathias Vetter

  • Understanding limit theorems for semimartingales: a short survey

    Mark Podolskij;Mathias Vetter

  • New tests for jumps in semimartingale models

    M. Podolskij;D. Ziggel

  • Multipower Variation for Brownian Semistationary Processes

    Ole E. Barndorff-Nielsen;José Manuel Corcuera;Mark Podolskij

  • Quantitative Breuer-Major Theorems

    Ivan Nourdin;Giovanni Peccati;Mark Podolskij

  • Limit theorems for functionals of higher order differences of Brownian semi-stationary processes

    Ole Barndorff-Nielsen;José Manuel Corcuera;Mark Podolskij

  • Quantitative Breuer-Major Theorems

    Mark Podolskij

Frequent Co-Authors

Ole E. Barndorff-Nielsen
Ole E. Barndorff-Nielsen Aarhus University
Jean Jacod
Jean Jacod Sorbonne University
Nakahiro Yoshida
Nakahiro Yoshida University of Tokyo
Holger Dette
Holger Dette Ruhr University Bochum
Per A. Mykland
Per A. Mykland University of Chicago
Giovanni Peccati
Giovanni Peccati University of Luxembourg
Nikolaus Hautsch
Nikolaus Hautsch University of Vienna
Ivan Nourdin
Ivan Nourdin University of Luxembourg
David Nualart
David Nualart University of Kansas
Neil Shephard
Neil Shephard Harvard University

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