collaborators

15 papers

math.ST2026

Weighted Nuclear Elastic Net Estimation of (Near-) Low-Rank Drift Matrices in Ornstein-Uhlenbeck Processes

Dmytro Marushkevych, Francisco Pina, Mark Podolskij

We study estimation of the drift matrix in a continuously observed high-dimensional Ornstein-Uhlenbeck process when the drift is exactly or approximately low rank. In this setting,…

econ.EM2026

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

Kim Christensen, Mark Podolskij, Mathias Vetter

This paper presents a Hayashi-Yoshida type estimator for the covariation matrix of continuous Itô semimartingales observed with noise. The coordinates of the multivariate process…

econ.EM2026

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

Kim Christensen, Silja Kinnebrock, Mark Podolskij

We show how pre-averaging can be applied to the problem of measuring the ex-post covariance of financial asset returns under microstructure noise and non-synchronous trading. A pre…

econ.EM2026

Asymptotic theory of range-based multipower variation

Kim Christensen, Mark Podolskij

In this paper, we present a realized range-based multipower variation theory, which can be used to estimate return variation and draw jump-robust inference about the diffusive vola…

econ.EM2026

Fact or friction: Jumps at ultra high frequency

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

This paper shows that jumps in financial asset prices are often erroneously identified and are, in fact, rare events accounting for a very small proportion of the total price varia…

econ.EM2026

Realized range-based estimation of integrated variance

Kim Christensen, Mark Podolskij

We provide a set of probabilistic laws for estimating the quadratic variation of continuous semimartingales with realized range-based variance -- a statistic that replaces every sq…