A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value

The transaction and market of bitcoin is volatile, meaning it’s uncertain because it changes frequently. There have been a number of research studies that have presented bitcoin price prediction models, but none of them have looked at the controlling variables linked with bitcoin transact...

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Autores principales:	Nahla Aljojo, Areej Alshutayri, Eman Aldhahri, Seita Almandeel, Azida Zainol
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Bitcoin (digital currency) volume of BTC bitcoin timestamp Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/83500273b98242c38141ec07e9ceabf8
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id	oai:doaj.org-article:83500273b98242c38141ec07e9ceabf8
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spelling	oai:doaj.org-article:83500273b98242c38141ec07e9ceabf82021-11-18T00:10:27ZA Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value2169-353610.1109/ACCESS.2021.3124629https://doaj.org/article/83500273b98242c38141ec07e9ceabf82021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9597552/https://doaj.org/toc/2169-3536The transaction and market of bitcoin is volatile, meaning it’s uncertain because it changes frequently. There have been a number of research studies that have presented bitcoin price prediction models, but none of them have looked at the controlling variables linked with bitcoin transaction timestamps. It might be that price is not the only key criteria influencing bitcoin transactions, or the available model for bitcoin price prediction is yet to consider timestamp as a determining factor in its transaction. A better and more accurate model would be required to predict how the Timestamp influences changes of bitcoin transactions. That is why this current study utilized a Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the prediction of timestamp influence on Bitcoin value. Bitcoin historical datasets which are converted to a nonlinear regression into a “well-formulated” statistical problem in the manner of a ridge regression are used. Simulation analysis indicates that bitcoin digital currency’s performance variation is highly influenced by its transaction timestamp with the prediction accuracy of 96%. The contributions of this research lies with the fact that specific Bitcoin transaction events repeat themselves over and over again, meaning that the Open-Price, High-Price, Low-Price, and Close-Price of Bitcoin price over timestamp developed a pattern that was predicted by NARX with less That means those involved in the transaction of bitcoin at the wrong timestamp will certainly face the uncertainty negative effect of the bitcoin market.Nahla AljojoAreej AlshutayriEman AldhahriSeita AlmandeelAzida ZainolIEEEarticleBitcoin (digital currency)volume of BTCbitcointimestampElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 148611-148624 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Bitcoin (digital currency) volume of BTC bitcoin timestamp Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Bitcoin (digital currency) volume of BTC bitcoin timestamp Electrical engineering. Electronics. Nuclear engineering TK1-9971 Nahla Aljojo Areej Alshutayri Eman Aldhahri Seita Almandeel Azida Zainol A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value
description	The transaction and market of bitcoin is volatile, meaning it’s uncertain because it changes frequently. There have been a number of research studies that have presented bitcoin price prediction models, but none of them have looked at the controlling variables linked with bitcoin transaction timestamps. It might be that price is not the only key criteria influencing bitcoin transactions, or the available model for bitcoin price prediction is yet to consider timestamp as a determining factor in its transaction. A better and more accurate model would be required to predict how the Timestamp influences changes of bitcoin transactions. That is why this current study utilized a Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the prediction of timestamp influence on Bitcoin value. Bitcoin historical datasets which are converted to a nonlinear regression into a “well-formulated” statistical problem in the manner of a ridge regression are used. Simulation analysis indicates that bitcoin digital currency’s performance variation is highly influenced by its transaction timestamp with the prediction accuracy of 96%. The contributions of this research lies with the fact that specific Bitcoin transaction events repeat themselves over and over again, meaning that the Open-Price, High-Price, Low-Price, and Close-Price of Bitcoin price over timestamp developed a pattern that was predicted by NARX with less That means those involved in the transaction of bitcoin at the wrong timestamp will certainly face the uncertainty negative effect of the bitcoin market.
format	article
author	Nahla Aljojo Areej Alshutayri Eman Aldhahri Seita Almandeel Azida Zainol
author_facet	Nahla Aljojo Areej Alshutayri Eman Aldhahri Seita Almandeel Azida Zainol
author_sort	Nahla Aljojo
title	A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value
title_short	A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value
title_full	A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value
title_fullStr	A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value
title_full_unstemmed	A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value
title_sort	nonlinear autoregressive exogenous (narx) neural network model for the prediction of timestamp influence on bitcoin value
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/83500273b98242c38141ec07e9ceabf8
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A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value

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