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New Fuzzy Approaches to Cryptocurrencies Investment Recommendation Systems

  • Vinícius Luiz Amaral
  • Emmanuel Tavares F. Affonso
  • Alisson Marques SilvaEmail author
  • Gray Farias Moita
  • Paulo Eduardo Maciel Almeida
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1000)

Abstract

This work proposes the use of Computational Intelligence algorithms to predict cryptocurrencies values based on historical values. After predicting the value of the currencies for up to three days following the current one using an evolving algorithm, two approaches were presented to suggest the investment: the first one uses only the result of the forecast to provide a suggestion of investment; in contrast, the second approach, in addition to using the prediction data returned by the evolving system, also applies a Mamdani system, based on expert knowledge, to suggest to the users what to do with their invested value. After performing and processing the historical data of three cryptocurrencies, the suggestions offered by both approaches were compared to the actual quote. The comparison presented results with a total assertiveness rate of over 90% for the three cryptocurrencies evaluated, according to established criteria, for both the evolving approach and the hybrid approach. Computational experiments suggest that the two proposed approaches are promising and competitive with alternatives reported in the literature.

Notes

Acknowledgements

This work was supported by Brazilian National Research Council (CNPq).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Vinícius Luiz Amaral
    • 1
  • Emmanuel Tavares F. Affonso
    • 1
  • Alisson Marques Silva
    • 1
    Email author
  • Gray Farias Moita
    • 1
  • Paulo Eduardo Maciel Almeida
    • 1
  1. 1.Graduate Program in Mathematical and Computational ModelingFederal Center for Technological Education of Minas Gerais – CEFET-MGBelo HorizonteBrazil

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