Heterogeneous component multiplicative error models for forecasting trading volumes

Antonio Naimoli and Giuseppe Storti

MPRA Paper from University Library of Munich, Germany

Abstract: We propose a novel approach to modelling and forecasting high frequency trading volumes. The new model extends the Component Multiplicative Error Model of Brownlees et al. (2011) by introducing a more flexible specification of the long-run component. This uses an additive cascade of MIDAS polynomial filters, moving at different frequencies, in order to reproduce the changing long-run level and the persistent autocorrelation structure of high frequency trading volumes. After investigating its statistical properties, the merits of the proposed approach are illustrated by means of an application to six stocks traded on the XETRA market in the German Stock Exchange.

Keywords: Intra-daily trading volume; dynamic component models; long-range dependence; forecasting. (search for similar items in EconPapers)
JEL-codes: C22 C53 C58 (search for similar items in EconPapers)
Date: 2019-05-09
New Economics Papers: this item is included in nep-bec, nep-ecm, nep-ets, nep-for, nep-mst and nep-ore
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Citations: View citations in EconPapers (1)

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Journal Article: Heterogeneous component multiplicative error models for forecasting trading volumes (2019)
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