The prediction of volatility is of primary importance for business applications in risk management, asset allocation and pricing of derivative instruments. This paper proposes a novel measurement model which takes into consideration the possibly time-varying interaction of realized volatility...

This paper studies the behaviour of crypto-currencies financial time-series of which Bitcoin is the most prominent example. The dynamic of those series is quite complex displaying extreme observations, asymmetries and several nonlinear characteristics which are difficult to model. We develop a...

This paper presents the R package MCS which implements the Model Confidence Set (MCS) procedure recently developed by Hansen, Lunde, and Nason (2011). The Hansen's procedure consists on a sequence of tests which permits to construct a set of "superior" models, where the null hypothesis of Equal...

We propose a new class of models specifi cally tailored for spatio-temporal data analysis. To this end, we generalize the spatial autoregressive model with autoregressive and heteroskedastic disturbances, i.e. SARAR(1,1), by exploiting the recent advancements in Score Driven (SD) models...