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Theses/Dissertations

2016

Academic -- UNF -- Master of Science in Computer and Information Sciences; Dissertations

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Challenging The Efficient Market Hypothesis With Dynamically Trained Artificial Neural Networks, Kevin M. Harper Jan 2016

Challenging The Efficient Market Hypothesis With Dynamically Trained Artificial Neural Networks, Kevin M. Harper

UNF Graduate Theses and Dissertations

A review of the literature applying Multilayer Perceptron (MLP) based Artificial Neural Networks (ANNs) to market forecasting leads to three observations: 1) It is clear that simple ANNs, like other nonlinear machine learning techniques, are capable of approximating general market trends 2) It is not clear to what extent such forecasted trends are reliably exploitable in terms of profits obtained via trading activity 3) Most research with ANNs reporting profitable trading activity relies on ANN models trained over one fixed interval which is then tested on a separate out-of-sample fixed interval, and it is not clear to what extent these …