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 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...

We introduce elements of Cumulative Prospect Theory into the portfolio selection problem and then compare stock portfolios selected under the behavioral approach with those selected according to classical approaches, such as Mean Variance and Mean Absolute Deviation ones. The mathematical...

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...