The aim of this note is to study the properties of some nonstationary autoregressive-moving average (ARMA) processes that are considered important in real world situations. In particular, the covariance structure and linear predictors are obtained.

In this paper we prove that the sum of two independent multivariate ARMA processes is also ARMA under certain regularity conditions.

A wide variety of conditional and stochastic variance models has been used to estimate latent volatility (or risk). In both the conditional and stochastic volatility literature, there has been some confusion between the definitions of asymmetry and leverage. In this paper, we first show the...

Most multivariate variance models suffer from a common problem, the “curse of dimensionalityâ€. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on multivariate models...

Several methods have recently been proposed in the ultra high frequency financial literature to remove the effects of microstructure noise and to obtain consistent estimates of the integrated volatility (IV) as a measure of ex-post daily volatility. Even bias-corrected and consistent realized...

This article reconsiders the relationship between stock return volatility and trading volume. Based on the multi-factor stochastic volatility model for stock return, we suggest several specifications for the trading volume. This approach enables the unobservable information arrival to follow the...

We provide a detailed summary of the large and vibrant emerging literature that deals with the multivariate modeling of conditional volatility of financial time series within the framework of stochastic volatility. The developments and achievements in this area represent one of the great success...

Modelling covariance structures is known to suffer from the curse of dimensionality. In order to avoid this problem for forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures that accommodates asymmetry and long memory....