The Markov Switching Acd Model
Johann Wolfgang Goethe-University, Finance & Accounting Working Paper No. 90
45 Pages Posted: 8 Nov 2002
Date Written: April 2002
We propose a new framework for modelling time dependence in duration processes on financial markets. The well known autoregressive conditional duration (ACD) approach introduced by Engle and Russell (1998) will be extended in a way that allows the conditional expectation of the duration process to depend on an unobservable stochastic process, which is modelled via a Markov chain. The Markov switching ACD model (MSACD) is a very flexible tool for description and forecasting of financial duration processes. In addition the introduction of an unobservable, discrete valued regime variable can be justified in the light of recent market microstructure theories. In an empirical application we show, that the MSACD approach is able to capture several specific characteristics of inter trade durations while alternative ACD models fail. Furthermore, we use the MSACD to test implications of a sequential trade model.
Keywords: Financial transaction data, autoregressive conditional duration models, nonlinear time series models, finite mixture distributions, Markov switching models, EM algorithm, market microstructure theory
JEL Classification: C22, C25, C41, G14
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