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Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes

Listed author(s):
  • Nikolaus Hautsch
  • Peter Malec
  • Melanie Schienle

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 on high frequencies, such as cumulated trading volumes or the time between potentially simultaneously occurring market events. 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 liquid NYSE stocks, we show that the model captures both the dynamic and distribution properties of the data very well and is able to correctly predict future distributions.

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File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2010-055.pdf
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Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2010-055.

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Length: 33 pages
Date of creation: Nov 2010
Handle: RePEc:hum:wpaper:sfb649dp2010-055
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