Coupling electrokinetics and iron nanoparticles for the remediation of contaminated soils

Fundação para a Ciência e a Tecnologia - PTDC/AGR-­AAM/101643/2008 NanoDC ; SFRH/BD/76070/2011 ; FP7-­PEOPLE-­IRSES-­2010-­269289-­ ELECTROACROSS

Using artificial neural networks to generate trading signals for crude oil, copper and gold futures

In this thesis, a feed-forward, back-propagating Artificial Neural Network using the gradient descent algorithm is developed to forecast the directional movement of daily returns for WTI, gold and copper futures. Out-of-sample back-test results vary, with some predictive abilities for copper futures but none for either WTI or gold. The best statistically significant hit rate achieved was 57% for copper with an absolute return Sharpe Ratio of 1.25 and a benchmarked Information Ratio of 2.11.