Method and system for artificial neural networks to predict price movements in the financial markets

The present invention relates to methods and systems for devising and implementing automated artificial neural networks to predict market performance and direction movements of the U.S. Treasury market, mortgage option-adjusted spreads (OAS), interest rate swap spreads, and U.S. Dollar/Mexican Peso exchange rate. The methods and systems of the present invention employ techniques used in actual neural networks naturally occurring in biological organisms to develop artificial neural network models for predicting movements in the financial market that are capable of extracting in a very consistent fashion non-linear relationships among input variables of the models that are readily apparent to the human traders.