Statistical inferences for price staleness

Aleksey Kolokolov, Giulia Livieri and Davide Pirino

Journal of Econometrics, 2020, vol. 218, issue 1, 32-81

Abstract: This paper proposes a nonparametric theory for statistical inferences on zero returns of high-frequency asset prices. Using an infill asymptotic design, we derive limit theorems for the percentage of zero returns observed on a finite time interval and for other related quantities. Within this framework, we develop two nonparametric tests. First, we test whether intra-day zero returns are independent and identically distributed. Second, we test whether intra-day variation of the likelihood of occurrence of zero returns can be solely explained by a deterministic diurnal pattern. In an empirical application to ten representative stocks of the NYSE, we provide evidence that the null of independent and identically distributed intra-day zero returns can be conclusively rejected. We further find that a deterministic diurnal pattern is not sufficient to explain the intra-day variability of the distribution of zero returns.

Keywords: Average staleness; Instantaneous price staleness; Liquidity; Zero returns; Stable convergence (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:218:y:2020:i:1:p:32-81

DOI: 10.1016/j.jeconom.2020.01.021

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