A simple linear alternative to multiplicative error models with an application to trading volume

Adam Clements, Stan Hurn and Vladimir Volkov ()
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Vladimir Volkov: Tasmanian School of Business & Economics, University of Tasmania, https://www.utas.edu.au/profiles/staff/economics/vladimir-volkov

No 2021-06, Working Papers from University of Tasmania, Tasmanian School of Business and Economics

Abstract: Forecasting intraday trading volume is an important problem in economics and finance. One influential approach to achieving this objective is the non-linear Component Multiplicative Error Model (CMEM) that captures time series dependence and intraday periodicity in volume. While the model is well suited to dealing with a non-negative time series, it is relatively cumbersome to implement. This paper proposes a system of linear equations, that is estimated using ordinary least squares, and provides at least as good a forecasting performance as that of the CMEM. This linear specification can easily be applied to model any time series that exhibits diurnal behaviour.

Keywords: Volume; forecasting; high-frequency data; CMEM; diurnal (search for similar items in EconPapers)
JEL-codes: C22 G00 (search for similar items in EconPapers)
Pages: 10 pages
Date: 2021
New Economics Papers: this item is included in nep-cwa, nep-ecm, nep-ets, nep-for and nep-ore
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Published by the University of Tasmania. Discussion paper 2021-06

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