loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: J. Mouton 1 and A. J. Hoffman 2

Affiliations: 1 North-West University, South Africa ; 2 Northwest University, South Africa

Keyword(s): Empirical Mode Decomposition (EMD), Artificial Neural Network, Foreign Exchange Rate Forecasting.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Domain Applications and Case Studies ; Enterprise Information Systems ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial, Financial and Medical Applications ; Methodologies and Methods ; Neural Network Software and Applications ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: This paper proposes a neural network based model applied to empirical mode decomposition (EMD) filtered data for multi-step-ahead prediction of exchange rates. EMD is used to decompose the returns of exchange rates into intrinsic mode functions (IMFs) which are partially recomposed to produce a low-pass filtered time series. This series is used to train a neural network for multi-step-ahead prediction. Out-of-sample tests on EUR/USD and USD/JPY rates show superior performance compared to random walk and neural network models that do not employ EMD filtering. The novel approach of using EMD as a filtering technique in combination with neural networks consistently delivers higher returns on investment and demonstrates its utility in multi-step-ahead prediction.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.119.162.226

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Mouton, J. and Hoffman, A. (2014). Combining Empirical Mode Decomposition with Neural Networks for the Prediction of Exchange Rates. In Proceedings of the International Conference on Neural Computation Theory and Applications (IJCCI 2014) - NCTA; ISBN 978-989-758-054-3, SciTePress, pages 244-249. DOI: 10.5220/0005130702440249

@conference{ncta14,
author={J. Mouton. and A. J. Hoffman.},
title={Combining Empirical Mode Decomposition with Neural Networks for the Prediction of Exchange Rates},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications (IJCCI 2014) - NCTA},
year={2014},
pages={244-249},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005130702440249},
isbn={978-989-758-054-3},
}

TY - CONF

JO - Proceedings of the International Conference on Neural Computation Theory and Applications (IJCCI 2014) - NCTA
TI - Combining Empirical Mode Decomposition with Neural Networks for the Prediction of Exchange Rates
SN - 978-989-758-054-3
AU - Mouton, J.
AU - Hoffman, A.
PY - 2014
SP - 244
EP - 249
DO - 10.5220/0005130702440249
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic