Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach
AbstractThis paper extends the stochastic conditional duration model first proposed by Bauwens and Veredas (2004) by imposing mixtures of bivariate normal distributions on the innovations of the observation and latent equations of the duration process. This extension allows the model not only to capture various density shapes of the durations but also to easily accommodate a richer dependence structure between the two innovations. In addition, it applies an estimation methodology based on the empirical characteristic function. Empirical applications based on the IBM and Boeing transaction data are provided to assess and illustrate the performance of the proposed model and the estimation method. One interesting empirical finding in this paper is that there is a significantly positive correlation under both the contemporaneous and lagged intertemporal dependence structures for the IBM and Boeing duration data. Copyright The Author 2011. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org, Oxford University Press.
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Bibliographic InfoArticle provided by Society for Financial Econometrics in its journal Journal of Financial Econometrics.
Volume (Year): 9 (2011)
Issue (Month): 3 (Summer)
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Other versions of this item:
- Dinghai Xu & John Knight & Tony S. Wirjanto, 2008. "Asymmetric Stochastic Conditional Duration Model --A Mixture of Normals Approach"," Working Papers 08007, University of Waterloo, Department of Economics.
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- Luc Bauwens & Pierre Giot, 2003.
"Asymmetric ACD models: Introducing price information in ACD models,"
Springer, vol. 28(4), pages 709-731, November.
- BAUWENS, Luc & GIOT, Pierre, . "Asymmetric ACD models: Introducing price information in ACD models," CORE Discussion Papers RP -1670, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Strickland, Chris M. & Forbes, Catherine S. & Martin, Gael M., 2006.
"Bayesian analysis of the stochastic conditional duration model,"
Computational Statistics & Data Analysis,
Elsevier, vol. 50(9), pages 2247-2267, May.
- Chris M. Strickland & Catherine S. Forbes & Gael M. Martin, 2003. "Bayesian Analysis of the Stochastic Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 14/03, Monash University, Department of Econometrics and Business Statistics.
- Yu, Jun, 2005.
"On leverage in a stochastic volatility model,"
Journal of Econometrics,
Elsevier, vol. 127(2), pages 165-178, August.
- Jun Yu, 2004. "On Leverage in a Stochastic Volatility Model," Working Papers 13-2004, Singapore Management University, School of Economics.
- Jun Yu, 2004. "On leverage in a stochastic volatility model," Econometric Society 2004 Far Eastern Meetings 497, Econometric Society.
- Jun Yu, 2004. "On Leverage in a Stochastic Volatility Model," Econometric Society 2004 Far Eastern Meetings 506, Econometric Society.
- John L. Knight & Stephen E. Satchell & Jun Yu, 2002. "Estimation of the Stochastic Volatility Model by the Empirical Characteristic Function Method," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 44(3), pages 319-335, 09.
- Bauwens, Luc & Veredas, David, 2004.
"The stochastic conditional duration model: a latent variable model for the analysis of financial durations,"
Journal of Econometrics,
Elsevier, vol. 119(2), pages 381-412, April.
- BAUWENS, Luc & VEREDAS, David, . "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," CORE Discussion Papers RP -1688, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Knight, John L. & Yu, Jun, 2002. "Empirical Characteristic Function In Time Series Estimation," Econometric Theory, Cambridge University Press, vol. 18(03), pages 691-721, June.
- John Knight & Cathy Q. Ning, 2008. "Estimation of the stochastic conditional duration model via alternative methods," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 593-616, November.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
- Tony S. Wirjanto & Adam W. Kolkiewicz & Zhongxian Men, 2013. "Stochastic Conditional Duration Models with Mixture Processes," Working Paper Series 29_13, The Rimini Centre for Economic Analysis.
- Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2013. "Bayesian Inference of Multiscale Stochastic Conditional Duration Models," Working Paper Series 63_13, The Rimini Centre for Economic Analysis.
- Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2013. "Bayesian Inference of Asymmetric Stochastic Conditional Duration Models," Working Paper Series 28_13, The Rimini Centre for Economic Analysis.
- Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
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