The design of financial trading systems (FTSs) is a subject of high interest both for the academic environment and for the professional one due to the promises by machine learning methodologies. In this paper we consider the Reinforcement Learning-based policy evaluation approach known as...

Several empirical studies have shown the inadequacy of the standard Brownian motion (sBm) as a model of asset returns. To correct for this evidence some authors have conjectured that asset returns may be independently and identically Pareto-Levy stable (PLs) distributed, whereas others have...

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...

The measurement of the quality of research has reached nowadays an increasing interest not only for scientific reasons but also for the critical problem of researchers' ranking, due to the lack of grant assignments. The most commonly used approach is based on the so-called $h$-index, even if the...

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...

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...