research-article

Forecasting of Bitcoin Daily Returns with EEMD-ELMAN based Model

Authors:

Rohaifa Khaldi,

Abdellatif El Afia,

Raddouane Chiheb,

Rdouan FaiziAuthors Info & Claims

LOPAL '18: Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications

Article No.: 20, Pages 1 - 6

https://doi.org/10.1145/3230905.3230948

Published: 02 May 2018 Publication History

Abstract

The present study investigates the application of EEMD-ELMAN model to forecast the daily returns of the Bitcoin. More than seven years data were collected online from 18th July 2010 to 17th January 2018. Then the data signal was decomposed into several sub-signals using EEMD method. After, sub-signals were captured by different ELMAN models, and their output results were combined to generate the final forecast. Besides, the results of this study were compared against ELMAN and ARGARCH models. Hence, the statistical metrics revealed that the used model outperforms ELMAN network, and has approximately the same estimation error as ARGARCH, although the later model is prone to bad generalization due to the high gap between its approximation and generalization errors. Therefore, we can confirm that EEMD can be considered as a promising preprocessing technique, which enables to bring up the forecasting performance of ELMAN network with respect to highly volatile time series.

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Digital Library

Cited By

Kumah S(2023)Cryptocurrency and African fiat currencies: A peaceful coexistence?Economic Notes10.1111/ecno.1222953:1Online publication date: 30-Sep-2023
https://doi.org/10.1111/ecno.12229
Bouzbita SAfia A(2022)A Fuzzy Meta Model for Adjusting Ant Colony System ParametersProceedings of the 5th International Conference on Big Data and Internet of Things10.1007/978-3-031-07969-6_4(48-58)Online publication date: 3-Jul-2022
https://doi.org/10.1007/978-3-031-07969-6_4
da Silva TFrancisquini RNascimento M(2021)Meteorological and human mobility data on predicting COVID-19 cases by a novel hybrid decomposition method with anomaly detection analysisExpert Systems with Applications: An International Journal10.1016/j.eswa.2021.115190182:COnline publication date: 15-Nov-2021
https://dl.acm.org/doi/10.1016/j.eswa.2021.115190
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Index Terms

Forecasting of Bitcoin Daily Returns with EEMD-ELMAN based Model
1. Applied computing
  1. Operations research
    1. Forecasting
2. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks

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cover image ACM Other conferences

LOPAL '18: Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications

May 2018

357 pages

ISBN:9781450353045

DOI:10.1145/3230905

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 02 May 2018

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LOPAL '18

LOPAL '18: Theory and Applications

May 2 - 5, 2018

Rabat, Morocco

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LOPAL '18 Paper Acceptance Rate 61 of 141 submissions, 43%;

Overall Acceptance Rate 61 of 141 submissions, 43%

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https://doi.org/10.1111/ecno.12229
Bouzbita SAfia A(2022)A Fuzzy Meta Model for Adjusting Ant Colony System ParametersProceedings of the 5th International Conference on Big Data and Internet of Things10.1007/978-3-031-07969-6_4(48-58)Online publication date: 3-Jul-2022
https://doi.org/10.1007/978-3-031-07969-6_4
da Silva TFrancisquini RNascimento M(2021)Meteorological and human mobility data on predicting COVID-19 cases by a novel hybrid decomposition method with anomaly detection analysisExpert Systems with Applications: An International Journal10.1016/j.eswa.2021.115190182:COnline publication date: 15-Nov-2021
https://dl.acm.org/doi/10.1016/j.eswa.2021.115190
Khaldi RAfia AChiheb R(2019)Performance prediction of pharmaceutical suppliersInternational Journal of Computer Applications in Technology10.1504/ijcat.2019.10117260:4(317-325)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1504/ijcat.2019.101172
Khaldi REl Afia AChiheb RLazaar MDuvallet CAl Achhab MMahboub OSilkan H(2019)Impact of Multistep Forecasting Strategies on Recurrent Neural Networks Performance for Short and Long HorizonsProceedings of the 4th International Conference on Big Data and Internet of Things10.1145/3372938.3372979(1-8)Online publication date: 23-Oct-2019
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Mezouar HEl Afia ALazaar MDuvallet CAl Achhab MMahboub OSilkan H(2019)A 4-level reference for self-adaptive processes based on SCOR and integrating Q-LearningProceedings of the 4th International Conference on Big Data and Internet of Things10.1145/3372938.3372953(1-5)Online publication date: 23-Oct-2019
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Khaldi RAfia AChiheb R(2019)Forecasting of weekly patient visits to emergency department: real case studyProcedia Computer Science10.1016/j.procs.2019.01.026148(532-541)Online publication date: 2019
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Khaldi REl Afia AChiheb R(2019)Forecasting of BTC volatility: comparative study between parametric and nonparametric modelsProgress in Artificial Intelligence10.1007/s13748-019-00196-wOnline publication date: 4-Jul-2019
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