A comparison of financial duration models via density forecasts
Bauwens, Luc Giot, Pierre Grammig, Joachim Veredas, David
Bauwens, Luc
Giot, Pierre
Grammig, Joachim
Veredas, David
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Publication Type
Journal article
Editor
Supervisor
Publication Year
2004-10
Journal
International Journal of Forecasting
Book
Publication Volume
20
Publication Issue
4
Publication Begin page
589
Publication End page
609
Publication Number of pages
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Abstract
Using density forecast evaluation techniques, we compare the predictive performance of econometric specifications that have been developed for modeling duration processes in intra-day financial markets. The model portfolio encompasses various variants of the Autoregressive Conditional Duration (ACD) model and recently proposed dynamic factor models. The evaluation is conducted on time series of trade, price and volume durations computed from transaction data of NYSE listed stocks. The results show that simpler approaches perform at least as well as more complex methods. With respect to modeling trade duration processes, standard ACD models successfully account for duration dynamics while none of the models provides an acceptable specification for the conditional duration distribution. We find that the Logarithmic ACD, if based on a flexible innovation distribution, provides a quite robust and useful framework for the modeling of price and volume duration processes.
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Keywords
38 Economics, 3801 Applied Economics, 3802 Econometrics