Intelligent Computation Applied to Mutual Fund Investment: A Genetic Algorithms Approach
نویسنده
چکیده
This dissertation presents a study of the portfolio management problem applied to mutual fund investments. An approach based on Genetic Algorithms is followed and three different heuristics are proposed to forecast the rise or fall of a mutual fund. These heuristics are based in the concepts of daily variations, relevant maximums and minimums and simple moving averages. A prototype developed in MATLAB is used for the testing and comparing of the heuristics. All three heuristics have outperformed the Buy-and-Hold strategy in the tests performed.
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