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339923

Bitcoin_ML: An Efficient Framework for Bitcoin Price Prediction Using Machine Learning

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Last updated: 24 Dec 2024

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Abstract

Econometrics can be used to understand and forecast price movements, assess market efficiency, and explore the factors influencing Bitcoin's value and adaptation.
Econometrics is related to bitcoin in seven categories: price analysis and prediction, market efficiency, determination of Bitcoin prices, risk analysis, adaptation and network effects, causality tests, and simulation and stress. Testing these analyses can be invaluable for policymakers, investors, and financial institutions interested in the economics of digital currencies.
Bitcoin price prediction in machine learning has many challenges that have deep roots in 2 main properties: cryptocurrencies and complexities in the Machine Learning models.
Many problems are associated with machine learning for bitcoin price prediction, such as overfitting, data quality and availability, latent variables, model interpretability, computational complexity, dynamic adaptation, market manipulation, anomalies, data snooping bias risk, and time horizon mismatch. In the paper, we proposed an efficient framework for the prediction of bitcoin using nine different machine learning algorithms (linear Regression, random forest, adaboost, tree, KNN, gradient boosting, constant, neural network, SVM) on five different datasets. The results revealed that linear Regression emerged as the optimal model for the first data set. In the second data set, the random forest model demonstrated superior performance. The third data set exhibited the highest efficacy when the Adaboost model was employed. The fourth data set yielded the best outcomes with the random forest model, while linear Regression was the most effective choice for the final data set. 

DOI

10.21608/jocc.2024.339923

Keywords

Bitcoin Price Prediction, Machine Learning, artificial intelligence, Algorithm, Linear Regression Random Forest

Authors

First Name

Maged

Last Name

Farouk

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

melsayed@aiu.edu.eg

City

Alamein

Orcid

-

First Name

Nashwa

Last Name

Shaker

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

nragab@aiu.edu.eg

City

Alamein

Orcid

-

First Name

Diaa

Last Name

AbdElminaam

MiddleName

s

Affiliation

Department of Data Science , Faculty of Computer Science , Misr International University , Cairo , Egypt

Email

diaa.salama@miuegypt.edu.eg

City

-

Orcid

0000-0002-1544-9906

First Name

Omnia

Last Name

Elrashidy

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

oelrashidy@aiu.edu.eg

City

Alamein

Orcid

-

First Name

Lana

Last Name

Mandour

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

lana.samir.2023@aiu.edu.eg

City

Alamein

Orcid

-

First Name

Malak

Last Name

Mesbah

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

malak.mostafa.2023@aiu.edu.eg

City

Alamein

Orcid

-

First Name

Jana

Last Name

Walid

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

jana.ibrahim.2023@aiu.edu.eg

City

Alamein

Orcid

-

First Name

Mariam

Last Name

Ahmed

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

mariam.mokbel.2023@aiu.edu.eg

City

Alamein

Orcid

-

First Name

Rawan

Last Name

Attia

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

rawan.awad.2023@aiu.edu.eg

City

Alamein

Orcid

-

First Name

Nouran

Last Name

Ahmed

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

nouran.hamid.2023@aiu.edu.eg

City

Alamein

Orcid

-

First Name

Reda

Last Name

Elazab

MiddleName

-

Affiliation

Department of Business Information Systems, Faculty of Business, Alamein International University, Alamein, Egypt

Email

relazab@aiu.edu.eg

City

Alamein

Orcid

-

Volume

3

Article Issue

1

Related Issue

45956

Issue Date

2024-01-01

Receive Date

2024-01-06

Publish Date

2024-02-02

Page Start

70

Page End

87

Online ISSN

2636-3577

Article File

JOCC_Volume 3_Issue 1_Pages 70-87.pdf

PDF . 2.0MB

Link

https://jocc.journals.ekb.eg/article_339923.html

Detail API

https://jocc.journals.ekb.eg/service?article_code=339923

Order

6

Type

Original Article

Type Code

731

Publication Type

Journal

Publication Title

Journal of Computing and Communication

Publication Link

https://jocc.journals.ekb.eg/

MainTitle

Bitcoin_ML: An Efficient Framework for Bitcoin Price Prediction Using Machine Learning

Details

Type

Article

Created At

24 Dec 2024