Ricerc@Sapienza

The paper presents an overview of global issues in optimizationmethods for training feedforward
neural networks (FNN) in a regression setting.We first recall the learning optimization
paradigm for FNN and we briefly discuss global scheme for the joint choice of the network
topologies and of the network parameters. The main part of the paper focuses on the
core subproblem which is the continuous unconstrained (regularized) weights optimization
problem with the aim of reviewing global methods specifically arising both in multi layer

A trading strategy simply consists in a procedure which defines conditions for buying or selling a security on a financial market. These decisions rely on the values of some indicators that, in turn, affect the tuning of the strategy parameters. The choice of these parameters significantly affects the performance of the trading strategy.