A comparison of financial duration models via density forecasts |
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Authors: | Luc Pierre Joachim David |
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Institution: | a CORE and Department of Economics, Université catholique de Louvain, Voie du Roman Pays, 34, B-1348, Louvain-La-Neuve, Belgium;b CORE and University of Namur, Rempart de la Vierge, 8, B-5000, Namur, Belgium;c University of Tübingen, Faculty of Economics, Mohlstr. 36, D-72074, Tübingen, Germany;d CORE and Center, Tilburg University, Department of Econometrics and OR P.O. Box 90153, 5000 Tilburg, The Netherlands |
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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: | Duration processes Transactions data Intra-day financial markets Density forecast evaluation |
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