A Bayesian Approach for Capturing Daily Heterogeneity in Intra-Daily Durations Time Series

32 Pages Posted: 9 Feb 2010 Last revised: 27 Nov 2012

See all articles by Christian T. Brownlees

Christian T. Brownlees

Universitat Pompeu Fabra - Faculty of Economic and Business Sciences; Barcelona Graduate School of Economics (Barcelona GSE)

Marina Vannucci

Rice University

Date Written: July 2012

Abstract

Intra-daily financial durations time series typically exhibit evidence of long range dependence. This has motivated the introduction of models able to reproduce this stylized fact, like the Fractionally Integrated Autoregressive Conditional Duration Model. In this work we introduce a novel specification able to capture long range dependence. We propose a three component model that consists of an autoregressive daily random effect, a semiparametric time-of-day effect and an intra-daily dynamic component: the Mixed Autoregressive Conditional Duration (Mixed ACD) model. The random effect component allows for heterogeneity in mean reversal within a day and captures low frequency dynamics in the duration time series.The joint estimation of the model parameters is carried out using MCMC techniques based on the Bayesian formulation of the model. The empirical application to a set of widely traded US tickers shows that the model is able to capture low frequency dependence in duration time series. We also find that the degree of dependence and dispersion of low frequency dynamics is higher in periods of higher financial distress.

Keywords: Financial Durations, ACD, MCMC

JEL Classification: C11, C14, C22

Suggested Citation

Brownlees, Christian T. and Vannucci, Marina, A Bayesian Approach for Capturing Daily Heterogeneity in Intra-Daily Durations Time Series (July 2012). Available at SSRN: https://ssrn.com/abstract=1550253 or http://dx.doi.org/10.2139/ssrn.1550253

Christian T. Brownlees (Contact Author)

Universitat Pompeu Fabra - Faculty of Economic and Business Sciences ( email )

Ramon Trias Fargas 25-27
Barcelona, 08005
Spain

HOME PAGE: http://84.89.132.1/~cbrownlees/

Barcelona Graduate School of Economics (Barcelona GSE) ( email )

Ramon Trias Fargas 25-27
Barcelona, Catalonia 08014
Spain

Marina Vannucci

Rice University ( email )

6100 South Main Street
Houston, TX 77005-1892
United States

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