This paper provides theoretical properties and Monte-Carlo studies of a stochastic conditional duration model with mixture-of-normal error distributions an effcient estimation approach via a continuous empirical characteristic function. The empirical version of this paper is studied in Xu,...

This paper extends the stochastic conditional duration model first proposed by Bauwens and Veredas (2004) by imposing mixtures of bivariate normal distributions on the innovations of the observation and latent equations of the duration process. This extension allows the model not only to capture...

This paper investigates the properties of a linearized stochastic volatility (SV) model originally from Harvey et al. (Rev Econ Stud 61:247–264, <CitationRef CitationID="CR20">1994</CitationRef>) under an extended flexible specification (discrete mixtures of normal). General closed form expressions for the moment conditions are derived....</citationref>

This article develops an efficient method for estimating the discrete mixtures of normal family based on the continuous empirical characteristic function (CECF). An iterated estimation procedure based on the closed form objective distance function is proposed to improve the estimation...