In this work we analyze and implement different Reinforcement Learning (RL) algorithms in financial trading system applications. RL-based algorithms applied to financial systems aim to find an optimal policy, that is an optimal mapping between the variables describing the state of the system and...

In this work we use a MultiCriteria Decision Analysis (MCDA) model to evaluate the creditworthiness of a sample of Italian Small and Medium-sized Enterprises (SMEs), on the basis of their balance sheet data provided by the AIDA database. Our methodology is able to consider simultaneously...

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 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 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...