Identification of Linear Movement in the Time Series of Ethereum Cryptocurrency Montly Transaction Volume through the SARIMA Model

Authors

  • Richard de Freitas Pinto Universidade Federal do Rio Grande
  • Viviane Leite Dias Mattos Universidade Federal do Rio Grande
  • Luiz Ricardo Nakamura Universidade Federal de Lavras https://orcid.org/0000-0002-7312-2717

DOI:

https://doi.org/10.14295/vetor.v33i1.15162

Keywords:

Time Series, Ethereum, SARIMA

Abstract

This work presents the modeling of the monthly volume of transactions of the Ethereum cryptocurrency through the Box-Jenkins methodology, involving the steps: exploratory analysis, identification, guarantee and validation, some of which performed using different techniques. The model found by the SARIMA modeling (Integrated autoregressive model of seasonal moving averages) was able to demonstrate the linear behavior of the data in a satisfactory way, but it was not enough to describe the behavior of the series, composed of linear and non-linear movement, being better represented by a hybrid model.

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Published

2023-06-28

How to Cite

de Freitas Pinto, R., Mattos, V. L. D., & Nakamura, L. R. (2023). Identification of Linear Movement in the Time Series of Ethereum Cryptocurrency Montly Transaction Volume through the SARIMA Model. VETOR - Journal of Exact Sciences and Engineering, 33(1), 97–104. https://doi.org/10.14295/vetor.v33i1.15162

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