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...

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-Lévy stable (PLs) distributed, whereas others have...

In this paper we propose an efficient initialization of a deterministic Particle Swarm Optimization (PSO) scheme. PSO has showed to be promising for solving several unconstrained global optimization problems from real applications, where derivatives are unavailable and the evaluation of the...

The purpose of this paper is to solve a stochastic control problem consisting of optimizing the management of a trading system. Two model free machine learning algorithms based on Reinforcement Learning method are compared: the Q-Learning and the SARSA ones. Both these models optimize their...

In a recent paper, a simple index able to evaluate the non-linear bivariate comovement between two asset prices has been proposed. In this paper we assess if that index satisfies the classical seven axioms formulated by Rényi that a measure of dependence should meet. Further, in the cases in...

1 Albano G. et al., A comparison among alternative parameters estimators in the Vasicek process: a small sample analysis -- 2 Amendola A. et al., On the use of mixed sampling in modelling realized volatility: The MEM–MIDAS -- 3 Amerise I. L. and Tarsitano A., Simultaneous prediction intervals...

Comovements among asset prices have received a lot of attention for several reasons. For example, comovements are important in cross-hedging and cross-speculation; they determine capital allocation both domestically and in international mean-variance portfolios and also, they are useful in...

Recent advances in natural language processing have contributed to the development of market sentiment measures through text content analysis in news providers and social media. The effectiveness of these sentiment variables depends on the implemented techniques and the type of source on which...