By: |
Naimoli, Antonio;
Storti, Giuseppe |
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. |
JEL: |
C22 C53 C58 |
Date: |
2019–05–09 |
URL: |
http://d.repec.org/n?u=RePEc:pra:mprapa:93802&r=all |