To estimate the probability of default of companies and the correlated rating classes, it is necessary to use efficiently the information contained in different databases. In this respect, we propose a novel approach, based on the recursive usage of Bayes theorem, that can be very helpful in...

Twitter text data may be very useful to predict financial tangibles, such as share prices, as well as intangible assets, such as company reputation. While twitter data are becoming widely available to researchers, methods aimed at selecting which twitter data are reliable are, to our knowledge,...

The measurement of the quality of academic research is a rather controversial issue. Recently Hirsch has proposed a measure that has the advantage of summarizing in a single summary statistics all the information that is contained in the citation counts of each scientist. From that seminal...

In this contribution we aim at improving ordinal variable selection in the context of causal models. In this regard, we propose an approach that provides a formal inferential tool to compare the explanatory power of each covariate, and, therefore, to select an effective model for classification...

In this contribution we aim at improving ordinal variable selection in the context of causal models. In this regard, we propose an approach that provides a formal inferential tool to compare the explanatory power of each covariate, and, therefore, to select an effective model for classification...

We treat the topic of the distribution of functionals of discrete ordinal variables. We focus on the probability mass functions of several summary measures and of two important L-estimators that can be profitably used in data analysis. What is proposed is illustrated by means of a practical...

Social media, such as blogs and on-line forums, contain a huge amount of information that is typically unorganized and fragmented. An important issue, that has been raising importance so far, is to classify on-line texts in order to detect possible anomalies. For example on-line texts...

Financial network models are a useful tool to model interconnectedness and systemic risks in financial systems. They are essentially descriptive, and based on highly correlated networks. In this paper we embed them in a stochastic framework, aimed at a more parsimonious and more realistic...

Systemic risk modelling concerns the estimation of the interrelationships between financial institutions, with the aim of establishing which of them are more central and, therefore, more contagious/subject to contagion. The aim of this paper is to develop a novel systemic risk model. A model...