While much of classical statistical analysis is based on Gaussian distributional assumptions, statistical modelling with the Laplace distribution has gained importance in many applied fields. This phenomenon is rooted in the fact that, like the Gaussian, the Laplace distribution has many...

The class of mixed normal conditional heteroskedastic (MixN-GARCH) models, which couples a mixed normal distributional structure with GARCH-type dynamics, has been shown to offer a plausible decomposition of the contributions to volatility, as well as excellent out-of-sample forecasting...

Many authors have observed what is known as the Taylor property, namely that the time series dependencies of financial volatility as measured by the autocorrelation function of power-transformed absolute returns are stronger for absolute stock returns than for the squares. In this note, we...

The goal of this paper is to illuminate the capability of the component GARCH model of Ding and Granger (1996) and Engle and Lee (1999) to reproduce the long memory-type behavior of financial volatility. The potential of this model to capture the long memory dynamics observed in measures of...