Statistical Inferences for Price Staleness

71 Pages Posted: 13 Nov 2018 Last revised: 21 Jan 2020

See all articles by Aleksey Kolokolov

Aleksey Kolokolov

University of Manchester - Manchester Business School

Giulia Livieri

Scuola Normale Superiore

Davide Pirino

Department of Economics and Finance, University of Rome "Tor Vergata"

Date Written: November 6, 2018

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: staleness, idle time, liquidity, zero returns, stable convergence

Suggested Citation

Kolokolov, Aleksey and Livieri, Giulia and Pirino, Davide, Statistical Inferences for Price Staleness (November 6, 2018). Available at SSRN: https://ssrn.com/abstract=3283628 or http://dx.doi.org/10.2139/ssrn.3283628

Aleksey Kolokolov (Contact Author)

University of Manchester - Manchester Business School ( email )

Booth Street West
Manchester, M15 6PB
United Kingdom

Giulia Livieri

Scuola Normale Superiore ( email )

Piazza dei Cavalieri, 7
Pisa, 56126
Italy

Davide Pirino

Department of Economics and Finance, University of Rome "Tor Vergata" ( email )

Via Columbia 2
Rome, Lazio 00133
Italy

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