Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros

Blasques Francisco (), Holý Vladimír () and Tomanová Petra ()
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Blasques Francisco: VU University Amsterdam and Tinbergen Institute, Amsterdam, The Netherlands
Holý Vladimír: Department of Econometrics, Prague University of Economics and Business, Prague, Czechia
Tomanová Petra: Department of Econometrics, Prague University of Economics and Business, Prague, Czechia

Studies in Nonlinear Dynamics & Econometrics, 2024, vol. 28, issue 5, 673-702

Abstract: In finance, durations between successive transactions are usually modeled by the autoregressive conditional duration model based on a continuous distribution omitting zero values. Zero or close-to-zero durations can be caused by either split transactions or independent transactions. We propose a discrete model allowing for excessive zero values based on the zero-inflated negative binomial distribution with score dynamics. This model allows to distinguish between the processes generating split and standard transactions. We use the existing theory on score models to establish the invertibility of the score filter and verify that sufficient conditions hold for the consistency and asymptotic normality of the maximum likelihood of the model parameters. In an empirical study, we find that split transactions cause between 92 % and 98 % of zero and close-to-zero values. Furthermore, the loss of decimal places in the proposed approach is less severe than the incorrect treatment of zero values in continuous models.

Keywords: financial high-frequency data; autoregressive conditional duration model; zero-inflated negative binomial distribution; generalized autoregressive score model (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1515/snde-2022-0008

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