Publication:
Fibonacci retracement pattern recognition for forecasting foreign exchange market

Simple item page
cris.author.scopus-author-id 57218511646
cris.author.scopus-author-id 38561331300
cris.author.scopus-author-id 7102137687
cris.author.scopus-author-id 55860800560
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtual.department Universiti Malaysia Perlis
cris.virtualsource.department 97249ac5-6bf2-440d-b171-28ee875c9f9c
cris.virtualsource.department be9cf5fc-8446-49dd-bdbc-dc013789a114
cris.virtualsource.department f706deee-19e1-46a5-a4e8-25c727ea8dbc
dc.contributor.author Mohd Fauzi Ramli
dc.contributor.author Ahmad Kadri Junoh
dc.contributor.author Mahyun Ab Wahab
dc.contributor.author Wan Zuki Azman Wan Muhamad
dc.date.accessioned 2024-09-27T04:01:08Z
dc.date.available 2024-09-27T04:01:08Z
dc.date.issued 2020-01-01
dc.description.abstract Fibonacci retracement implicates a forecast of future movements in foreign exchange rates (forex) of the previous movement inductive analysis. Fibonacci ratios are used to forecast the retracements level of 0.382, 0.500 and 0.618 and to determine the current trend which provide the mathematical foundation for the Elliott wave theory. K-nearest neighbour (KNN) and linear discriminant analysis (LDA) algorithm are the pattern recognition method for nonlinear feature mining of Elliott wave patterns. Results show that LDA is better than KNN in terms of classification accuracy data which are 99.43%. Among of three levels of Fibonacci retracement results, the 38.2% shows the best forecasting for Great Britain Pound pair to US Dollar currency as major pair by using mean absolute error (MAE), root mean square error (RMSE) and pearson correlation coefficient (r) as the statistical measurements which are 0.001884, 0.000019 and 0.992253 for uptrend and 0.001685, 0.000019 and 0.998806 for downtrend.
dc.identifier.doi 10.1504/IJBIDM.2020.108775
dc.identifier.scopus 2-s2.0-85089366826
dc.identifier.uri https://hdl.handle.net/20.500.14170/4404
dc.identifier.uri https://www.inderscience.com/offers.php?id=108775
dc.language.iso en
dc.relation.funding Ministry of Higher Education, Malaysia
dc.relation.grantno undefined
dc.relation.ispartof International Journal of Business Intelligence and Data Mining
dc.relation.ispartofseries International Journal of Business Intelligence and Data Mining
dc.relation.issn 17438187
dc.subject Elliott wave
dc.subject Fibonacci retracement
dc.subject Forecast
dc.subject Forex
dc.subject Golden ratio
dc.title Fibonacci retracement pattern recognition for forecasting foreign exchange market
dc.type Resource Types::text::journal::journal article
dspace.entity.type Publication
oaire.citation.endPage 178
oaire.citation.issue 2
oaire.citation.startPage 159
oaire.citation.volume 17
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
oairecerif.author.affiliation Universiti Malaysia Perlis
person.identifier.orcid #PLACEHOLDER_PARENT_METADATA_VALUE#
person.identifier.orcid #PLACEHOLDER_PARENT_METADATA_VALUE#
person.identifier.orcid #PLACEHOLDER_PARENT_METADATA_VALUE#
person.identifier.orcid #PLACEHOLDER_PARENT_METADATA_VALUE#
person.identifier.scopus-author-id 57218511646
person.identifier.scopus-author-id 38561331300
person.identifier.scopus-author-id 7102137687
person.identifier.scopus-author-id 55860800560
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Fibonacci retracement pattern recognition for forecasting foreign exchange market.pdf
Size:
447.95 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Publications 2020