Research interests and PhD projects
Alessandra's research is mainly focused on time series models. In particular, she is working on non-linear models for time-varying parameters of conditional densities. According to the parameter or quantity of interest (e.g. mean, scale, quantiles), to the specific research problem addressed (e.g. signal extraction, volatility forecasting, conditional density estimation) and to the data at hand (univariate, multivariate, high-dimensional, spatio-temporal data) different problems arise. Some of these problems are concerned with: optimal filtering of non-Gaussian models; robust filtering; asymptotic theory under non-standard assumptions; stochastic properties of dynamic models; quasi score-driven models.
Potential PhD students interested in a project on these topics are welcome to contact Alessandra by email.