In this paper, a new class of polarization measures is derived axiomatically. The concept of polarization is here identified with the decline of the middle class. In particular, we extend the definition of middle class towards a more realistic framework: the middle class is defined in terms of...

Building predictive models for genomic mining requires feature selection, as an essential preliminary step to reduce the large number of variable available. Feature selection is a process to select a subset of features which is the most essential for the intended tasks such as classification,...

We consider the problem of estimating the lifetime value of customers, when a large number of features are present in the data. In order to measure lifetime value we use survival analysis models to estimate customer tenure. In such a context, a number of classical modelling challenges arise. We...

Operational risk is hard to quantify, for the presence of heavy tailed loss distributions. Extreme value distributions, used in this context, are very sensitive to the data, and this is a problem in the presence of rare loss data. Self risk assessment questionnaires, if properly modelled, may...

In this paper we propose a novel approach to measure risks, when the data available are expressed in an ordinal scale. As a result we obtain a new index of risk bounded between 0 and 1, that leads to a risk ordering that is consistent with a stochastic dominance approach. The proposed measure,...

Model uncertainty remains a challenge to researchers in different applications. When many competing models are available for estimation, and without enough guidance from theory, model averaging represents an alternative to model selection. Despite model averaging approaches have been present in...

This paper proposes a novel methodology for integrating nan- cial risk and operational risk. In order to demonstrate the approach, we use real data from a telecommunication company providing services to enterprises in dierent business lines and geographical locations. For each enterprise, we...

Building predictive models for genomic mining requires feature selection, as an essential preliminary step to reduce the large number of variable available. Feature selection is a process to select a subset of features which is the most essential for the intended tasks such as classification,...

We consider the problem of estimating the lifetime value of customers, when a large number of features are present in the data. In order to measure lifetime value we use survival analysis models to estimate customer tenure. In such a context, a number of classical modelling challenges arise. We...