Bayesian Inference of Multiscale Stochastic Conditional Duration Models

Posted: 3 Sep 2014

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: September 1, 2014

Abstract

In this paper we revisit the notion that a single factor of duration running on single time scale is adequate to capture the dynamics of the duration process of financial transaction data. The documented poor fit of the left tail of the marginal distribution of the observed durations in some existing one-factor stochastic duration models may be indicative of the possible existence of multiple stochastic duration factors running on different time scales. This paper proposes multiscale stochastic conditional duration (MSCD) models to describe the dynamics of duration of financial transaction data. Suitable algorithms of MCMC are developed to fit the resulting MSCD models under three distributional assumptions about the innovation of the measurement equation. Simulation studies suggest that our proposed models and methods result in improved in-sample fits as well as improved duration forecasts. Applications of our models and methods to two duration data sets of FIAT and IBM indicate the existence of at least two factors governing the dynamics of the duration of the stock transactions.

Keywords: Markov Chain Monte Carlo; Multiscale; Auxiliary particle filter; Probability integral transform; Deviance information criterion.

JEL Classification: C10; C41; G10

Suggested Citation

Wirjanto, Tony S. and Men, Zhongxian and Kolkiewicz, Adam, Bayesian Inference of Multiscale Stochastic Conditional Duration Models (September 1, 2014). Available at SSRN: https://ssrn.com/abstract=2490013

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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