A (semi-)parametric functional coefficient autoregressive conditional duration model
AbstractIn this paper, we propose a class of ACD-type models that accommodatesoverdispersion, intermittent dynamics, multiple regimes, and sign and size asymme-tries in financial durations. In particular, our functional coefficient autoregressive con-ditional duration (FC-ACD) model relies on a smooth-transition autoregressive speci-fication. The motivation lies on the fact that the latter yields a universal approximationif one lets the number of regimes grows without bound. After establishing that the suf-ficient conditions for strict stationarity do not exclude explosive regimes, we addressmodel identifiability as well as the existence, consistency, and asymptotic normality ofthe quasi-maximum likelihood (QML) estimator for the FC-ACD model with a fixednumber of regimes. In addition, we also discuss how to consistently estimate using asieve approach a semiparametric variant of the FC-ACD model that takes the numberof regimes to infinity. An empirical illustration indicates that our functional coefficientmodel is flexible enough to model IBM price durations.
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