In the classical model for portfolio selection the risk is measured by the variance of returns. It is well known that, if returns are not elliptically distributed, this may cause inaccurate investment decisions. To address this issue, several alternative measures of risk have been proposed. In...

In this paper a particular multicriteria decision aid approach is used in order to evaluate the creditworthiness of a set of about 14,000 Italian firms viewed as potential applicants for bank loans in the 2006-2008 period. The methodology is able to consider simultaneously all factors affecting...

In this paper we use an evolutionary approach in order to infer the values of the parameters (weights of criteria, preference, indifference and veto thresholds) for developing the multicriteria method MURAME. According to the logic of preference disaggregation, the problem consists in finding...

In this paper the use of Artificial Neural Networks (ANNs) in on-line booking for hotel industry is investigated. The paper details the description, the modeling and the resolution technique of on-line booking. The latter problem is modeled using the paradigms of machine learning, in place of...

Counterfeiting is a well known world-wide phenomenon afflicting several real economies. Notwithstanding the importance of this topic, there are not many works about it in the literatute; moreover, these contributions mainly deal with counterfeiting employing a model developed in a static time...

In this work we analyze the effects of credit contagion on the credit quality of a portfolio of bank loans issued to SMEs. To this aim we start from the discrete time model proposed in Barro and Basso (2005), that considers the counterparty risk generated by the business relations in a network...

In this contribution we analyze two models for the joint probability of defaults of dependent credit risks that are based on a generalisation of Polya urn scheme. In particular we focus our attention on the problems related to the maximum likelihood estimation of the parameters involved, and to...

We propose a class of preconditioners for symmetric linear systems arising from numerical analysis and nonconvex optimization frameworks. Our preconditioners are specifically suited for large indefinite linear systems and may be obtained as by-product of Krylov-subspace solvers, as well as by...

In this paper we analyze some issues related to the general problem of information spreading among individuals, where suitable assumptions on the information exchange are considered. In particular, starting from the scheme proposed in [5], which is based on a majority rule to treat the...

We consider the solution of bound constrained optimization problems, where we assume that the evaluation of the objective function is costly, its derivatives are unavailable and the use of exact derivativefree algorithms may imply a too large computational burden. There is plenty of real...