Realized drift

Sébastien Laurent (), Roberto Renò and Shuping Shi
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Sébastien Laurent: AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, IUF - Institut universitaire de France - M.E.N.E.S.R. - Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche
Roberto Renò: ESSEC Business School
Shuping Shi: Macquarie University [Sydney]

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Abstract: Drift and volatility are two mainsprings of asset price dynamics. While volatilities have been studied extensively in the literature, drifts are commonly believed to be impossible to estimate and largely ignored in the literature. This paper shows how to detect drift using realized autocovariance implemented on high-frequency data. We use a theoretical treatment in which the classical model for the efficient price, an Itō semimartingale possibly contaminated by microstructure noise, is enriched with drift and volatility explosions. Our theory advocates a novel decomposition for realized variance into a drift and a volatility component, which leads to significant improvements in volatility forecasting.

Keywords: Volatility Forecasting; Serial Covariance; High-frequency Data; Drift (search for similar items in EconPapers)
Date: 2026
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Published in Journal of Econometrics, inPress, pp.105813. ⟨10.1016/j.jeconom.2024.105813⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05443560

DOI: 10.1016/j.jeconom.2024.105813

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