  Computational techniques have shown much promise in the field of Finance,
owing to their ability to extract sense out of dauntingly complex systems. This
paper reviews the most promising of these techniques, from traditional
computational intelligence methods to their machine learning siblings, with
particular view to their application in optimising the management of a
portfolio of financial instruments. The current state of the art is assessed,
and prospective further work is assessed and recommended
