Threshold Stochastic Conditional Duration Model for Transaction Data

Posted: 3 Sep 2014 Last revised: 1 Jan 2015

See all articles by Tony S. Wirjanto

Tony S. Wirjanto

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

Zhongxian Men

Independent

Adam Kolkiewicz

Independent

Date Written: December 31, 2014

Abstract

This paper proposes a threshold stochastic conditional duration (SCD) model for financial data at the transaction level. In addition to assuming that the innovations of the duration process follow a threshold distribution with positive support, we also assume that the latent first-order autoregressive process of the log conditional durations switches between two regimes. The regimes are determined by the levels of the observed durations and the threshold SCD model is specified to be self-excited. Markov Chain Monte Carlo methods within a Bayesian framework are then developed for parameter estimation. For model comparison, we employ a deviance information criteria, which does not depend on the number of model parameters directly. Duration forecasting is constructed by using an auxiliary particle filter based on the fitted models. Simulation studies demonstrate that our proposed model and estimation approach work well in terms of parameter estimation and duration forecasting. Lastly the proposed models and estimation approach are applied to two benchmark data sets that have been studied in the literature, namely IBM and Boeing transaction data.

Keywords: Stochastic conditional duration; Threshold; Bayesian inference; Markov Chain Monte Carlo; Probability integral transform; Deviance information criterion

JEL Classification: C10; C41; G10

Suggested Citation

Wirjanto, Tony S. and Men, Zhongxian and Kolkiewicz, Adam, Threshold Stochastic Conditional Duration Model for Transaction Data (December 31, 2014). Available at SSRN: https://ssrn.com/abstract=2490147

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

Zhongxian Men

Independent ( email )

Adam Kolkiewicz

Independent ( email )

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