A class of autoregressive moving-average (ARMA) models proposed by Jorgensen and Song [Journal of Applied Probability (1998), Vol. 35, pp. 78-92] with exponential dispersion model margins are useful to deal with non-normal stationary time series with high-order autocorrelation. One property...

This paper proposes a threshold stochastic conditional duration (SCD) model for financial data at the transaction level. In addition to assuming that the innovations of the duration process follow a threshold distribution with positive support, we also assume that the latent first-order...

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 discusses how conditional heteroskedasticity models can be estimated efficiently without imposing strong distributional assumptions such as normality. Using the generalized method of moments (GMM) principle, we show that for a class of models with a symmetric conditional distribution,...