Asymmetric Stochastic Conditional Duration Model --A Mixture of Normals Approach"
John Knight and
Tony Wirjanto ()
No 8007, Working Papers from University of Waterloo, Department of Economics
This 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.
Keywords: Stochastic Conditional Duration model; Leverage Effect; Discrete Mixtures of Normal; Empirical Characteristic Function (search for similar items in EconPapers)
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Journal Article: Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:wat:wpaper:08007
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