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      Hokohoko: A comprehensive framework for evaluating artificial intelligence-based and statistical techniques for foreign exchange speculation

      Bradley, Neil Christopher
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      Bradley, N. C. (2020). Hokohoko: A comprehensive framework for evaluating artificial intelligence-based and statistical techniques for foreign exchange speculation (Thesis, Master of Science (Research) (MSc(Research))). The University of Waikato, Hamilton, New Zealand. Retrieved from https://hdl.handle.net/10289/13752
      Permanent Research Commons link: https://hdl.handle.net/10289/13752
      Abstract
      This thesis investigates the measurement of predictor performance as applied to foreign exchange speculation. It outlines the development of key ideas and techniques over the course of the last 120 years, and examines the datasets and metrics used within a representative sample of the academic corpus. In this examination two problems are identified: first, there is a lack of consistency in the datasets used to test researchers’ algorithms; and second, a large variety of metrics are used, most of which are either inappropriate for or inappropriately applied to FOREX speculation. To address these issues, this thesis presents two solutions: a Python library, Hokohoko, which provides a consistent dataset and interface for testing FOREX prediction algorithms; and a new metric, Speculative Accuracy, which it argues provides a more appropriate measure of usefulness with regards to speculation. Hokohoko is then used to test a series of hypotheses regarding the usefulness of various metrics, alongside Speculative Accuracy.
      Date
      2020
      Type
      Thesis
      Degree Name
      Master of Science (Research) (MSc(Research))
      Supervisors
      Mayo, Michael
      Patros, Panos
      Publisher
      The University of Waikato
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      All items in Research Commons are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.
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      • Masters Degree Theses [2146]
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