Asymmetric Stochastic Conditional Duration Model — A Mixture-of-Normal Approach

Journal of Financial Econometrics, Vol. 9, No. 3, 469-488, 2011

Posted: 31 Mar 2013

See all articles by Dinghai Xu

Dinghai Xu

Independent

John Knight

University of Western Ontario, Faculty of Social Science, Deparment of Economics (Deceased)

Tony S. Wirjanto

University of Waterloo - School of Accounting and Finance; University of Waterloo, Department of Statistics & Actuarial Science

Date Written: 2011

Abstract

This 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.

Keywords: Stochastic Duration Model, Mixture of Normal Distribution, Leverage Effect, Continuous Empirical Characteristic Function

JEL Classification: G12, C51, C22, C13

Suggested Citation

Xu, Dinghai and Knight, John L. and Wirjanto, Tony S., Asymmetric Stochastic Conditional Duration Model — A Mixture-of-Normal Approach (2011). Journal of Financial Econometrics, Vol. 9, No. 3, 469-488, 2011, Available at SSRN: https://ssrn.com/abstract=2241818

Dinghai Xu

Independent ( email )

John L. Knight

University of Western Ontario, Faculty of Social Science, Deparment of Economics (Deceased)

Tony S. Wirjanto (Contact Author)

University of Waterloo - School of Accounting and Finance ( email )

200 University Avenue West
Waterloo, Ontario N2L 3G1
Canada
519-888-4567 x35210 (Phone)

HOME PAGE: http://https://uwaterloo.ca/statistics-and-actuarial-science/people-profiles/tony-wirjanto

University of Waterloo, Department of Statistics & Actuarial Science ( email )

200 University Avenue West
Waterloo, Ontario N2L 3G1
Canada
519-888-4567 x35210 (Phone)
519-746-1875 (Fax)

HOME PAGE: http://math.uwaterloo.ca/statistics-and-actuarial-science/people-profiles/tony-wirjanto

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