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Open Access Green as soon as Postprint is submitted to ZB.
When frictions are fractional: Rough noise in high-frequency data.
J. Am. Stat. Assoc., DOI: 10.1080/01621459.2024.2428466 (2025)
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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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
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
Publisher
Taylor & Francis
Publishing Place
530 Walnut Street, Ste 850, Philadelphia, Pa 19106 Usa
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Epidemiology (EPI)