This paper addresses the question of the selection of multivariate GARCH models in terms of variance matrix forecasting accuracy with a particular focus on relatively large scale problems. We consider 10 assets from NYSE and NASDAQ and compare 125 model based one-step-ahead conditional variance...

We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set 248 multivariate models that differ in their...

This paper surveys the most important developments in multivariate ARCH-type modelling. It reviews the model specifications, the inference methods, and the main areas of application of these models in financial econometrics.

A large number of parameterizations have been proposed to model conditional variance dynamics in a multivariate framework. This paper examines the ranking of multivariate volatility models in terms of their ability to forecast out-of-sample conditional variance matrices. We investigate how...

This paper proposes a class of asymmetric Autoregressive Conditional Duration models, which extends the ACD model of Engle and Russell (1997). The asymmetry consists of letting the duration process depend on the state of the price process in the beginning and at the end of the each duration. If...

This paper introduces the logarithmic autoregressive conditional duration model (Log-ACD model). The logarithmic version allows for more flexibility than the ACD model of Engle and Russel (1995), when additional variables are included in the model. We apply the Log-ACD model to bid/ask prices...

This paper proposes a class of asymmetric Autoregressive Conditional Duration models, which extends the ACD model of Engle and Russell (1997). The asymmetry consists of letting the duration process depend on the state of the price process in the beginning and at the end of each duration. If the...

A new model for the analysis of durations, the stochastic conditional duration (SCD) model, is introduced. This model is based of the assumption that the durations are generated by a latent stochastic factor that follows a first order autoregressive process. The latent factor is pertubed...

This paper introduces the logarithmic autoregressive conditional duration model (log-ACD model). The logarithmic version allows for more flexibilitythan the ACD model of Engel and Russel (1995), when additional variables are included in the model. We apply the log-ACD model to bid/ask prices...

A new model for the analysis of durations, the stochastic conditional dusration (SCD) model is introduced. This model is based on the assumption that the durations are generated by a latent stochastic factor that follows a first order autoregressive process. The lattent factor is perturbed...