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 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...