Capturing the zero: a new class of zero-augmented distributions and multiplicative error processes

  • We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed at high frequencies, such as cumulated trading volumes. We introduce a flexible point-mass mixture distribution and develop a semiparametric specification test explicitly tailored for such distributions. Moreover, we propose a new type of multiplicative error model (MEM) based on a zero-augmented distribution, which incorporates an autoregressive binary choice component and thus captures the (potentially different) dynamics of both zero occurrences and of strictly positive realizations. Applying the proposed model to high-frequency cumulated trading volumes of both liquid and illiquid NYSE stocks, we show that the model captures the dynamic and distributional properties of the data well and is able to correctly predict future distributions.

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Metadaten
Author:Nikolaus HautschORCiDGND, Peter MalecGND, Melanie SchienleORCiDGND
URN:urn:nbn:de:hebis:30:3-228731
Parent Title (German):Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2011,25
Series (Serial Number):CFS working paper series (2011, 25)
Document Type:Working Paper
Language:English
Year of Completion:2011
Year of first Publication:2011
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2011/10/07
Tag:Excess Zeros; High-Frequency Data; Market Microstructure; Multiplicative Error Model; Point-Mass Mixture; Semiparametric Specification Test
Issue:Version June 2011
Page Number:37
HeBIS-PPN:279890907
Institutes:Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS)
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
JEL-Classification:C Mathematical and Quantitative Methods / C1 Econometric and Statistical Methods: General / C14 Semiparametric and Nonparametric Methods
C Mathematical and Quantitative Methods / C1 Econometric and Statistical Methods: General / C16 Specific Distributions
C Mathematical and Quantitative Methods / C2 Single Equation Models; Single Variables / C22 Time-Series Models; Dynamic Quantile Regressions (Updated!)
C Mathematical and Quantitative Methods / C2 Single Equation Models; Single Variables / C25 Discrete Regression and Qualitative Choice Models; Discrete Regressors (Updated!)
C Mathematical and Quantitative Methods / C5 Econometric Modeling / C51 Model Construction and Estimation
Licence (German):License LogoDeutsches Urheberrecht