Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/79578 
Year of Publication: 
2012
Series/Report no.: 
SFB 649 Discussion Paper No. 2012-031
Publisher: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Abstract: 
We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time. Analyzing one-minute cumulative trading volumes of five large NASDAQ stocks in 2008, we show that local windows of approximately 3 to 4 hours are reasonable to capture parameter variations while balancing modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM where local estimation windows are fixed on an ad hoc basis.
Subjects: 
multiplicative error model
local adaptive modelling
high-frequency processes
trading volume
forecasting
JEL: 
C41
C51
C53
G12
G17
Document Type: 
Working Paper

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