TY  - RPRT
A1  - Hujer, Reinhard
A1  - Kokot, Stefan
A1  - Vuletić, Sandra
T1  - Comparison of MSACD models
N2  - 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. JEL classification: C22, C25, C41, G14
KW  - Financial transaction data
KW  - autoregressive conditional duration(ACD) models
KW  - nonlinear time series models
KW  - finite mixture distributions
Y1  - 2005
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/3221
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30-21889
IS  - This version: January 10, 2003
ER  -