@article{Lima2024,
abstract = {In this work, we develop specific models to predict the behavior of the Bitcoin cryptocurrency using a public database (Yahoo! Finance) to track price trends. The methodologies used are ARIMA and NNAR, and the validation of the models is carried out based on the daily closing values of assets. Both models fail to differ significantly. However, the adjusted model NNAR (2.2) fits slightly better with the original data series, presenting an MPE (Mean Percentage Error) of -0.102. Some prospects on the seasonality of data are discussed.},
author = {Lima, Patr{\'{i}}cia Virg{\'{i}}nia de Santana and da Cruz, David Ven{\^{a}}ncio and Sanz, Albaro Ramon Paiva},
doi = {https://doi.org/10.51359/2965-4661.2024.265073},
journal = {Socioeconomic Analytics},
keywords = {Bitcoin,NNAR,Time Series Analysis,forecast. ARIMA,prediction},
number = {1},
pages = {121--129},
title = {{Predicting Bitcoin Cryptocurrency Price Behavior based on ARIMA and NNAR modelling}},
url = {https://doi.org/10.51359/2965-4661.2024.265073},
volume = {2},
year = {2024}
}