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Chong, C.H.* ; Delerue, T. ; Mies, F.*

Rate-optimal estimation of mixed semimartingales.

Ann. Stat. 53, 219-244 (2025)
Postprint DOI
Open Access Green
Consider the sum Y = B + B(H) of a Brownian motion B and an independent fractional Brownian motion B(H) with Hurst parameter H ∈ (0, 1). Even though B(H) is not a semimartingale, it was shown by Cheridito (Bernoulli 7 (2001) 913–934) that Y is a semimartingale if H > 3/4. Moreover, Y is locally equivalent to B in this case, so H cannot be consistently estimated from local observations of Y. This paper pivots on another unexpected feature in this model: if B and B(H) become correlated, then Y will never be a semimartingale, and H can be identified, regardless of its value. This and other results will follow from a detailed statistical analysis of a more general class of processes called mixed semimartingales, which are semiparametric extensions of Y with stochastic volatility in both the martingale and the fractional component. In particular, we derive consistent estimators and feasible central limit theorems for all parameters and processes that can be identified from high-frequency observations. We further show that our estimators achieve optimal rates in a minimax sense.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Central Limit Theorem ; High-frequency Observations ; Hurst Parameter ; Kl Divergence ; Minimax Rate ; Mixed Fractional Brownian Motion ; Rough Noise
Sprache englisch
Veröffentlichungsjahr 2025
HGF-Berichtsjahr 2025
ISSN (print) / ISBN 0090-5364
Quellenangaben Band: 53, Heft: 1, Seiten: 219-244 Artikelnummer: , Supplement: ,
Verlag Institute of Mathematical Statistics (IMS)
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epidemiology (EPI)
POF Topic(s) 30202 - Environmental Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-504091-001
Scopus ID 85219079855
Erfassungsdatum 2025-05-06