This paper proposes a new time-deformation model for stock returns sampled in transaction time and directed by a generalized duration process. Stochastic volatility in this model is driven by an observed duration process and a latent autoregressive process. Parameter estimation in the model is...

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...

The dynamic analysis of corporate credit ratings is needed for predicting the risk included in a credit portfolio at different horizons. In this paper, we present the estimation of an ordered probit model with factors for the migration probabilities, with its application to aggregate data...

This article proposes stochastic conditional duration (SCD) models with quot;leverage effectquot; for financial transaction data, which extends both the autoregressive conditional duration (ACD) model (Engle and Russell, 1998, Econometrica, 66, 1127-1162) and the existing SCD model (Bauwens and...

This paper concerns goodness-of-fit test for semiparametric copula models. Our contribution is two-fold: we first propose a new test constructed via the comparison between "in-sample" and "out-of-sample" pseudolikelihoods, which avoids the use of any probability integral transformations. Under...

We propose a new class of state space models for longitudinal discrete response data where the observation equation is specified in an additive form involving both deterministic and random linear predictors. These models allow us to explicitly address the effects of trend, seasonal or other...