LOCAL ADAPTIVE MULTIPLICATIVE ERROR MODELS FOR HIGH-FREQUENCY FORECASTS
Article first published online: 27 JAN 2014
Copyright © 2014 John Wiley & Sons, Ltd.
Journal of Applied Econometrics
How to Cite
Härdle, W. K., Hautsch, N. and Mihoci, A. (2014), LOCAL ADAPTIVE MULTIPLICATIVE ERROR MODELS FOR HIGH-FREQUENCY FORECASTS. J. Appl. Econ.. doi: 10.1002/jae.2376
- Article first published online: 27 JAN 2014
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. Analysing 1-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. Copyright © 2014 John Wiley & Sons, Ltd.