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Heterogeneous component multiplicative error models for forecasting trading volumes

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  • Naimoli, Antonio
  • Storti, Giuseppe

Abstract

We propose a novel approach to the modelling and forecasting of 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, to reproduce the changing long-run level and the persistent autocorrelation structure of high-frequency trading volumes. After investigating the statistical properties of the proposed approach, we illustrate its merits by means of an application to six stocks that are traded on the XETRA market in the German Stock Exchange.

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  • Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    • Handle: RePEc:eee:intfor:v:35:y:2019:i:4:p:1332-1355
    DOI: 10.1016/j.ijforecast.2019.06.002
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    Cited by:

    1. Clements, Adam & Hurn, Stan & Volkov, Vladimir, 2021. "A simple linear alternative to multiplicative error models with an application to trading volume," Working Papers 2021-06, University of Tasmania, Tasmanian School of Business and Economics.

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    More about this item

    Keywords

    Intra-daily trading volume; Dynamic component models; Long-range dependence; Forecasting; MIDAS;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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