Asymmetric Stochastic Conditional Duration Model --A Mixture of Normals Approach"
AbstractThis paper extends the stochastic conditional duration model 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 the asymmetric behavior of the expected duration but also to easily accommodate a richer dependence structure between the two innovations. In addition, it proposes a novel estimation methodology based on the empirical characteristic function. A set of Monte Carlo experiments as well as 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 main empirical finding in this paper is that there is a signicantly positive "leverage effect" under both the contemporaneous and lagged inter-temporal de pendence structures for the IBM and Boeing duration data.
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Bibliographic InfoPaper provided by University of Waterloo, Department of Economics in its series Working Papers with number 08007.
Date of creation: Dec 2008
Date of revision:
Stochastic Conditional Duration model; Leverage Effect; Discrete Mixtures of Normal; Empirical Characteristic Function;
Other versions of this item:
- Dinghai Xu & John Knight & Tony S. Wirjanto, 2011. "Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(3), pages 469-488, Summer.
- NEP-ALL-2009-01-03 (All new papers)
- NEP-ECM-2009-01-03 (Econometrics)
- NEP-ORE-2009-01-03 (Operations Research)
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