Statistical inferences for price stalenessCitation formats

Standard

Statistical inferences for price staleness. / Kolokolov, Aleksey; Livieri, Giulia; Pirino, Davide.

In: Journal of Econometrics, Vol. 218, No. 1, 01.09.2020, p. 32-81.

Research output: Contribution to journalArticlepeer-review

Harvard

Kolokolov, A, Livieri, G & Pirino, D 2020, 'Statistical inferences for price staleness', Journal of Econometrics, vol. 218, no. 1, pp. 32-81. https://doi.org/10.1016/j.jeconom.2020.01.021

APA

Kolokolov, A., Livieri, G., & Pirino, D. (2020). Statistical inferences for price staleness. Journal of Econometrics, 218(1), 32-81. https://doi.org/10.1016/j.jeconom.2020.01.021

Vancouver

Kolokolov A, Livieri G, Pirino D. Statistical inferences for price staleness. Journal of Econometrics. 2020 Sep 1;218(1):32-81. https://doi.org/10.1016/j.jeconom.2020.01.021

Author

Kolokolov, Aleksey ; Livieri, Giulia ; Pirino, Davide. / Statistical inferences for price staleness. In: Journal of Econometrics. 2020 ; Vol. 218, No. 1. pp. 32-81.

Bibtex

@article{ca21722ea3c34c71b64592b4c4921fd7,
title = "Statistical inferences for price staleness",
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, Stable convergence, Zero returns",
author = "Aleksey Kolokolov and Giulia Livieri and Davide Pirino",
note = "Funding Information: We are indebted to the editor Yacine Ait-Sahalia and two anonymous reviewers for their useful comments. We warmly thank Jean Jacod and Roberto Ren? for helpful comments on a first version of the manuscript. We are grateful to Federico M. Bandi, Fulvio Corsi, Loriana Pelizzon and seminar participants at the University Ca? Foscari of Venice, University of Pisa, Research Centre SAFE, the 10th International Conference of the ERCIM WG on Computational and Methodological Statistics (London, December 16?18, 2017), the XI SoFiE Annual Conference (Lugano, June 12?14, 2018), the 11th International Conference of the ERCIM WG on Computational and Methodological Statistics (Pisa, December 14?16, 2018), the Quantitative Finance Workshop Qfw2019 (Z?rich, January 23?25, 2019). Aleksey Kolokolov acknowledges the support in the framework of the Trans-Atlantis Platform from the DFG, Germany under PE 2574/1-1 and the research support from the Research Center SAFE, funded by the State of Hessen initiative for research LOEWE, Germany. Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) ? Projekt nummer 329107530 Giulia Livieri acknowledges the support by Unicredit S.P.A., Italy under the project ?Dynamics and Information Research Institute-Quantum Information (Teoria dell'Informazione), Quantum Technologies?. Davide Pirino acknowledges partial support via the RBSI14DDNN, ?A new measure of liquidity?, financed within the program ?Scientific Independence of Young Researchers? of the Italian Ministry of Education and Research. All errors are our own. Publisher Copyright: {\textcopyright} 2020 Elsevier B.V. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2020",
month = sep,
day = "1",
doi = "10.1016/j.jeconom.2020.01.021",
language = "English",
volume = "218",
pages = "32--81",
journal = "Journal of Econometrics",
issn = "0304-4076",
publisher = "Elsevier BV",
number = "1",

}

RIS

TY - JOUR

T1 - Statistical inferences for price staleness

AU - Kolokolov, Aleksey

AU - Livieri, Giulia

AU - Pirino, Davide

N1 - Funding Information: We are indebted to the editor Yacine Ait-Sahalia and two anonymous reviewers for their useful comments. We warmly thank Jean Jacod and Roberto Ren? for helpful comments on a first version of the manuscript. We are grateful to Federico M. Bandi, Fulvio Corsi, Loriana Pelizzon and seminar participants at the University Ca? Foscari of Venice, University of Pisa, Research Centre SAFE, the 10th International Conference of the ERCIM WG on Computational and Methodological Statistics (London, December 16?18, 2017), the XI SoFiE Annual Conference (Lugano, June 12?14, 2018), the 11th International Conference of the ERCIM WG on Computational and Methodological Statistics (Pisa, December 14?16, 2018), the Quantitative Finance Workshop Qfw2019 (Z?rich, January 23?25, 2019). Aleksey Kolokolov acknowledges the support in the framework of the Trans-Atlantis Platform from the DFG, Germany under PE 2574/1-1 and the research support from the Research Center SAFE, funded by the State of Hessen initiative for research LOEWE, Germany. Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) ? Projekt nummer 329107530 Giulia Livieri acknowledges the support by Unicredit S.P.A., Italy under the project ?Dynamics and Information Research Institute-Quantum Information (Teoria dell'Informazione), Quantum Technologies?. Davide Pirino acknowledges partial support via the RBSI14DDNN, ?A new measure of liquidity?, financed within the program ?Scientific Independence of Young Researchers? of the Italian Ministry of Education and Research. All errors are our own. Publisher Copyright: © 2020 Elsevier B.V. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/9/1

Y1 - 2020/9/1

N2 - 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.

AB - 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.

KW - Average staleness

KW - Instantaneous price staleness

KW - Liquidity

KW - Stable convergence

KW - Zero returns

U2 - 10.1016/j.jeconom.2020.01.021

DO - 10.1016/j.jeconom.2020.01.021

M3 - Article

VL - 218

SP - 32

EP - 81

JO - Journal of Econometrics

JF - Journal of Econometrics

SN - 0304-4076

IS - 1

ER -