Comparison of alternative ACD models via density and interval forecasts: Evidence from the Australian stock market
David Allen,
Zdravetz Lazarov,
Michael McAleer and
Shelton Peiris
Mathematics and Computers in Simulation (MATCOM), 2009, vol. 79, issue 8, 2535-2555
Abstract:
In this paper a number of alternative autoregressive conditional duration (ACD) models are compared using a sample of data for three major companies traded on the Australian Stock Exchange. The comparison is performed by employing the methodology for evaluating density and interval forecasts, developed by Diebold et al. [F. Diebold, A. Gunther, S. Tay, Evaluating density forecasts with applications to financial risk management, International Economic Review 39 (1998) 863–883] and Christoffersen [P. Christoffersen, Evaluating interval forecasts, International Economic Review 39 (1998) 841–862], respectively. Our main finding is that the generalized gamma and log-normal distributions for the error terms have similar performance and perform better that the exponential and Weibull distributions. Additionally, there seems to be no substantial difference between the standard ACD specification of Engle and Russel [R. Engle, J. Russell, Autoregressive conditional duration: a new model for irregularly-spaced transaction data, Econometrica 66 (1998) 1127–1162] and the log-ACD specification of Bauwens and Giot [L. Bauwens, P. Giot, The logarithmic ACD model: an application to the bid-ask quote process of three NYSE stocks, Annales d’Economie et de Statistique 60 (2000) 117–150].
Keywords: ACD models; Comparison; Forecasts; Australia (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (11)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:79:y:2009:i:8:p:2535-2555
DOI: 10.1016/j.matcom.2008.12.014
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