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Chong, C.H.* ; Delerue, T. ; Li, G.*

When frictions are fractional: Rough noise in high-frequency data.

J. Am. Stat. Assoc. 120, 1531-1544 (2025)
DOI
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
The analysis of high-frequency financial data is often impeded by the presence of noise. This article is motivated by intraday return data in which market microstructure noise appears to be rough, that is, best captured by a continuous-time stochastic process that locally behaves as fractional Brownian motion. Assuming that the underlying efficient price process follows a continuous It & ocirc; semimartingale, we derive consistent estimators and asymptotic confidence intervals for the roughness parameter of the noise and the integrated price and noise volatilities, in all cases where these quantities are identifiable. In addition to desirable features such as serial dependence of increments, compatibility between different sampling frequencies and diurnal effects, the rough noise model can further explain divergence rates in volatility signature plots that vary considerably over time and between assets. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Hurst parameter; Market microstructure noise; Mixed fractional Brownian motion; Mixed semimartingales; Volatility estimation; Volatility signature plot; Microstructure Noise; Integrated Volatility; Generalized-method; Asymptotic Theory; Dynamics; Moments
ISSN (print) / ISBN 0162-1459
e-ISSN 1537-274X
Zeitschrift Journal of the American Statistical Association
Quellenangaben Band: 120, Heft: , Seiten: 1531-1544 Artikelnummer: , Supplement: ,
Verlag Taylor & Francis
Verlagsort 530 Walnut Street, Ste 850, Philadelphia, Pa 19106 Usa
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epidemiology (EPI)