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

  • Hurwitz E
  • Marwala T
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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. 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

Author-supplied keywords

  • black-scholes
  • difference
  • genetic algorithm
  • genetic programming
  • investment theory
  • learning
  • markowitz portfolio theory
  • network
  • neural
  • portfolio optimisation
  • reinforcement
  • temporal

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  • Evan Hurwitz

  • Tshilidzi Marwala

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