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

State of the Art Review for Applying Computational Intelligence and Machine Learning Techniques to Portfolio Optimisation