This paper studies the behavior of cryptocurrencies' financial time series, of which Bitcoin is
the most prominent example. The dynamics of these series are quite complex, displaying …

We investigate information-theoretic optimality properties of the score function of the
predictive likelihood as a device for updating a real-valued time-varying parameter in a …

We propose a new Markov switching model with time‐varying transitions probabilities. The
novelty of our model is that the transition probabilities evolve over time by means of an …

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 …

The construction of score-driven filters for nonlinear time series models is described, and
they are shown to apply over a wide range of disciplines. Their theoretical and practical …

We establish strong consistency and asymptotic normality of the maximum likelihood
estimator for stochastic time-varying parameter models driven by the score of the predictive …

We study the performances of alternative methods for calculating in-sample confidence and
out-of-sample forecast bands for time-varying parameters. The in-sample bands reflect …

We develop new multi-factor dynamic copula models with time-varying factor loadings and
observation-driven dynamics. The new models are highly flexible, scalable to high …

This chapter provides a survey of various multivariate GARCH specifications that model the
temporal dependence in the second moment of multivariate return series processes. The …

This paper develops a new class of dynamic models for forecasting extreme financial risk.
This class of models is driven by the score of the conditional distribution with respect to both …