The aim of this paper is to identify whether the GARCH or the SV based models provide the best goodness of fit to financial time-series data. To investigate the issue, three different formulations for each type (i.e., the standard model, the fat-tailed model, and the asymmetric model) are...

The statistical analysis of financial time series is a rich and diversified research field whose inherent complexity requires an interdisciplinary approach, gathering together several disciplines, such as statistics, economics, and computational sciences. This special issue of the Journal of...

This paper builds and implements multifactor stochastic volatility models for the international oil/energy markets (Brent oil and WTI oil) for the period 2011-2021. The main objective is to make step ahead volatility predictions for the front month contracts followed by an implication discussion...

We investigate several promising algorithms, proposed in literature, devised to detect sudden changes (structural breaks) in the volatility of financial time series. Comparative study of three techniques: ICSS, NPCPM and Cheng's algorithm is carried out via numerical simulation in the case of...

In this paper we introduce the STAR-STGARCH model that can characterizenonlinear behaviour both in the conditional mean and the conditionalvariance. A modelling cycle for this family of models, consisting ofspecification, estimation, and evaluation stages is constructed.Misspecification tests...