Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling
The development of models to predict the behavior of the Bitcoin cryptocurrency, using a public database (Yahoo! Finance) to predict price trends. The models used were ARIMA and NNAR with the validation of the models being carried out based on the daily closing values of the asset. Both models did...
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| Format: | Article |
| Language: | English |
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Universidade Federal de Pernambuco (UFPE)
2024-12-01
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| Series: | Socioeconomic Analytics |
| Subjects: | |
| Online Access: | https://periodicos.ufpe.br/revistas/index.php/SECAN/article/view/265073 |
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| _version_ | 1825201943439474688 |
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| author | Patricia Virginia de Santana Lima David Venâncio da Cruz Albaro Ramon Paiva Sanz |
| author_facet | Patricia Virginia de Santana Lima David Venâncio da Cruz Albaro Ramon Paiva Sanz |
| author_sort | Patricia Virginia de Santana Lima |
| collection | DOAJ |
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The development of models to predict the behavior of the Bitcoin cryptocurrency, using a public database (Yahoo! Finance) to predict price trends. The models used were ARIMA and NNAR with the validation of the models being carried out based on the daily closing values of the asset. Both models did not differ significantly, however the adjusted model NNAR (2.2) had a slightly better fit to the original data series, presenting an MPE (Mean Percentage Error) of -0.102.
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| format | Article |
| id | doaj-art-c373f14643a24cee937e7adc54192e1d |
| institution | Kabale University |
| issn | 2965-4661 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Universidade Federal de Pernambuco (UFPE) |
| record_format | Article |
| series | Socioeconomic Analytics |
| spelling | doaj-art-c373f14643a24cee937e7adc54192e1d2025-02-07T17:46:08ZengUniversidade Federal de Pernambuco (UFPE)Socioeconomic Analytics2965-46612024-12-012110.51359/2965-4661.2024.265073Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modellingPatricia Virginia de Santana Lima0https://orcid.org/0009-0005-4746-830XDavid Venâncio da Cruz1https://orcid.org/0000-0002-6290-7623Albaro Ramon Paiva Sanz2https://orcid.org/0000-0001-6697-8229State University of ParaíbaState University of ParaíbaState University of Paraíba The development of models to predict the behavior of the Bitcoin cryptocurrency, using a public database (Yahoo! Finance) to predict price trends. The models used were ARIMA and NNAR with the validation of the models being carried out based on the daily closing values of the asset. Both models did not differ significantly, however the adjusted model NNAR (2.2) had a slightly better fit to the original data series, presenting an MPE (Mean Percentage Error) of -0.102. https://periodicos.ufpe.br/revistas/index.php/SECAN/article/view/265073ARIMANNARTime Series AnalysisBitcoinprediction |
| spellingShingle | Patricia Virginia de Santana Lima David Venâncio da Cruz Albaro Ramon Paiva Sanz Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling Socioeconomic Analytics ARIMA NNAR Time Series Analysis Bitcoin prediction |
| title | Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling |
| title_full | Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling |
| title_fullStr | Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling |
| title_full_unstemmed | Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling |
| title_short | Predicting bitcoin cryptocurrency price behavior based on ARIMA and NNAR modelling |
| title_sort | predicting bitcoin cryptocurrency price behavior based on arima and nnar modelling |
| topic | ARIMA NNAR Time Series Analysis Bitcoin prediction |
| url | https://periodicos.ufpe.br/revistas/index.php/SECAN/article/view/265073 |
| work_keys_str_mv | AT patriciavirginiadesantanalima predictingbitcoincryptocurrencypricebehaviorbasedonarimaandnnarmodelling AT davidvenanciodacruz predictingbitcoincryptocurrencypricebehaviorbasedonarimaandnnarmodelling AT albaroramonpaivasanz predictingbitcoincryptocurrencypricebehaviorbasedonarimaandnnarmodelling |