Sistema híbrido para tomada de decisão em investimentos no mercado de criptomoedas

Translated title of the contribution: Hybrid system for decision making in investments in the cryptocurrency market

Juan G. Lazo Lazo, Gonzalo H. Herrera Medina, Luciana Faletti Almeida, Álvaro Talavera

Research output: Contribution to journalArticle in a journalpeer-review

Abstract

The cryptocurrency markets have been attracting attention and attracting all types of investors, from people to financial institutions that seek high returns due to the significant variation in prices and their rapid appreciation. However, this market is characterized by the level of volatility and uncertainty, leading the prices to very high levels and low levels; these characteristics generate great difficulty in investment managers' decision-making. This article proposes a hybrid system for decision making in investment management in the cryptocurrency market, considering a conservative investment profile, which seeks to reduce risk and maximize return on investment. The methodology aims, based on the historical price of cryptocurrencies, to establish return levels and estimate the probabilities of the transition of returns for each level; this is done based on the analysis of Markov chains, which are integrated into the multiple decision trees to identify the cryptocurrency that projects the greatest future return, considering that it will be sold in one or two periods after the acquisition. The results are compared with the real data, and the efficiency of the methodology is verified.
Translated title of the contributionHybrid system for decision making in investments in the cryptocurrency market
Original languagePortuguese
Pages (from-to)19577-19593
Number of pages17
JournalBrazilian Journal of Development
Volume7
Issue number2
DOIs
StatePublished - 2021
EventCongresso Brasileiro de Automática - Brasil
Duration: 11 Jan 202011 Jan 2020

Keywords

  • Cryptocurrencies
  • Investment management
  • Investment decision
  • Markov Chains
  • Decision Trees

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