In this paper, we investigate the out-of-sample forecasting ability of a genetic program to approach the dynamic evolution of the Yen/US$ and Pound Sterling/US$ exchange rates, and verify whether the method can beat the random walk model. Later on, we use the predicted values to generate a...

The mixture of two already known soft computing technics, like Genetic Algorithms and Neural Networks (NN) in Financial modeling, takes a new approach in the search for the best variables involving an Econometric model using a Neural Network. This new approach helps to recognice the importance...

The performance of Monte Carlo integration methods like importance-sampling or Markov-Chain Monte-Carlo procedures depends greatly on the choice of the importance- or candidate-density. Such a density must typically be "close" to the target density to yield numerically accurate results with...

Barr and Saraceno (JEDC, forthcoming) model the firm as a type of artificial neural network (ANN) which plays a repeated Cournot game. Each period, the network/firm must estimate the relationship between environmental conditions and optimal output. Among other results, the paper develops the...

Multi-currency instruments are quite popular in Iceland. This stems from the fact that loans based on the Icelandic Krona have high interest rates. Therefore, corporations and corporate customers often prefer to take loans in foreign currencies. In order to minimize the currency risk it is...

An efficient procedure is proposed to evaluate option prices using neural networks. The method considers alternatives to the procedures suggested by Hutchinson, Lo and Poggio in the Journal of Finance of 1994