Local Adaptive Multiplicative Error Models for High- Frequency Forecasts
SFB 649 Discussion Paper No. 2012-031
33 Pages Posted: 25 Aug 2013
Date Written: 2012
We propose a local adaptive multiplicative error model (MEM) accommodating time-varying 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.
Keywords: multiplicative error model, local adaptive modeling, high-frequency processes, trading volume, forecasting
JEL Classification: C41, C51, C53, G12, G17
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