Loading…
Metamorphosing forex: advancements in volatility forecasting using a modified fuzzy time series framework
The interplay of exchange rates among nations significantly influences both international and domestic trade, underscoring the pivotal role of the foreign exchange market (Forex) in a country's economic landscape. Forex fluctuations have a significant impact on the everyday lives of both govern...
Saved in:
| Published in: | Journal of big data 2024-10, Vol.11 (1), p.143-16, Article 143 |
|---|---|
| Main Authors: | , , , , , , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Citations: | Items that this one cites |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | |
|---|---|
| cites | cdi_FETCH-LOGICAL-c339t-f1e2fb087ac43ac489771bd39f9e38eaf9b17fcfd142de0d0836f46e4d513d403 |
| container_end_page | 16 |
| container_issue | 1 |
| container_start_page | 143 |
| container_title | Journal of big data |
| container_volume | 11 |
| creator | Bilal, Muhammad Aamir, Muhammad Abdullah, Saleem Norrulashikin, Siti Mariam Alqasem, Ohud A. Elwahab, Maysaa E. A. Khan, Ilyas |
| description | The interplay of exchange rates among nations significantly influences both international and domestic trade, underscoring the pivotal role of the foreign exchange market (Forex) in a country's economic landscape. Forex fluctuations have a significant impact on the everyday lives of both government agencies and the public population, directly influencing a country's prosperity or misfortune. This work proposes an advanced fuzzy time series model that incorporates domain universe sub-partitioning, parameter adjustment optimization methodologies, and interval forecasting methods. We utilized this model to examine annual exchange rate patterns between the Pakistani rupee (PKR) and the US dollar (US$), comparing its forecast accuracy to that of other models. Our proposed methodology outperformed existing methodologies in terms of forecasting precision, providing stakeholders with valuable insights for making informed, data-driven business decisions that benefit both individual firms and the country overall. |
| doi_str_mv | 10.1186/s40537-024-01003-7 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_fb88bbdb055c4ff8b6dae10d946a385a</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_fb88bbdb055c4ff8b6dae10d946a385a</doaj_id><sourcerecordid>3116758709</sourcerecordid><originalsourceid>FETCH-LOGICAL-c339t-f1e2fb087ac43ac489771bd39f9e38eaf9b17fcfd142de0d0836f46e4d513d403</originalsourceid><addsrcrecordid>eNp9kU1v1DAQhiPUSlSlf4CTJc6hM7ETO9xQxUelIi70bE3i8eJlEy-2t7D99aQbBJw4WGONnue1pbeqXiK8RjTddVbQSl1Do2pAAFnrZ9VFg31XI2J79s_9eXWV8xYAUC5Opy6q8IkLTTHtv8Yc5o3wMfHPN4LcA80jTzyXLMIsHuKOStiFcjwRI-XyRB9ODokpuuADO-EPj49HUcLEInMKnIVPNPGPmL69qM497TJf_Z6X1f37d19uPtZ3nz_c3ry9q0cp-1J75MYPYDSNSi7H9Frj4GTve5aGyfcDaj96h6pxDA6M7LzqWLkWpVMgL6vbNddF2tp9ChOlo40U7GkR08ZSKmHcsfWDMcPgBmjbUXlvhs4RI7hedSRNS0vWqzVrn-L3A-dit_GQ5uX7ViJ2ujUa-oVqVmpMMefE_s-rCPapIbs2ZJeG7KkhqxdJrlJe4HnD6W_0f6xfQ3SWKg</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3116758709</pqid></control><display><type>article</type><title>Metamorphosing forex: advancements in volatility forecasting using a modified fuzzy time series framework</title><source>ABI/INFORM global</source><source>Publicly Available Content Database</source><source>Springer Nature - SpringerLink Journals - Fully Open Access </source><source>Social Science Premium Collection (Proquest) (PQ_SDU_P3)</source><source>Coronavirus Research Database</source><creator>Bilal, Muhammad ; Aamir, Muhammad ; Abdullah, Saleem ; Norrulashikin, Siti Mariam ; Alqasem, Ohud A. ; Elwahab, Maysaa E. A. ; Khan, Ilyas</creator><creatorcontrib>Bilal, Muhammad ; Aamir, Muhammad ; Abdullah, Saleem ; Norrulashikin, Siti Mariam ; Alqasem, Ohud A. ; Elwahab, Maysaa E. A. ; Khan, Ilyas</creatorcontrib><description>The interplay of exchange rates among nations significantly influences both international and domestic trade, underscoring the pivotal role of the foreign exchange market (Forex) in a country's economic landscape. Forex fluctuations have a significant impact on the everyday lives of both government agencies and the public population, directly influencing a country's prosperity or misfortune. This work proposes an advanced fuzzy time series model that incorporates domain universe sub-partitioning, parameter adjustment optimization methodologies, and interval forecasting methods. We utilized this model to examine annual exchange rate patterns between the Pakistani rupee (PKR) and the US dollar (US$), comparing its forecast accuracy to that of other models. Our proposed methodology outperformed existing methodologies in terms of forecasting precision, providing stakeholders with valuable insights for making informed, data-driven business decisions that benefit both individual firms and the country overall.</description><identifier>ISSN: 2196-1115</identifier><identifier>EISSN: 2196-1115</identifier><identifier>DOI: 10.1186/s40537-024-01003-7</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>American dollar ; Astronomical models ; Autoregressive integrated moving average ; Average forecast error rate ; Big Data ; Central banks ; Communications Engineering ; Computational Science and Engineering ; Computer Science ; Currency ; Data Mining and Knowledge Discovery ; Database Management ; Decision making ; Economic development ; Economic growth ; Economic statistics ; Forecasting ; Forecasting techniques ; Foreign exchange markets ; Foreign exchange rates ; Forex ; Fuzzy sets ; Fuzzy time series ; Global economy ; Information Storage and Retrieval ; International trade ; Mathematical Applications in Computer Science ; Networks ; Parameter modification ; Set theory ; Time series ; Trends</subject><ispartof>Journal of big data, 2024-10, Vol.11 (1), p.143-16, Article 143</ispartof><rights>The Author(s) 2024</rights><rights>The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c339t-f1e2fb087ac43ac489771bd39f9e38eaf9b17fcfd142de0d0836f46e4d513d403</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/3116758709?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,11668,21374,25732,27903,27904,33590,36039,36991,38495,43712,43874,44342,44569</link.rule.ids></links><search><creatorcontrib>Bilal, Muhammad</creatorcontrib><creatorcontrib>Aamir, Muhammad</creatorcontrib><creatorcontrib>Abdullah, Saleem</creatorcontrib><creatorcontrib>Norrulashikin, Siti Mariam</creatorcontrib><creatorcontrib>Alqasem, Ohud A.</creatorcontrib><creatorcontrib>Elwahab, Maysaa E. A.</creatorcontrib><creatorcontrib>Khan, Ilyas</creatorcontrib><title>Metamorphosing forex: advancements in volatility forecasting using a modified fuzzy time series framework</title><title>Journal of big data</title><addtitle>J Big Data</addtitle><description>The interplay of exchange rates among nations significantly influences both international and domestic trade, underscoring the pivotal role of the foreign exchange market (Forex) in a country's economic landscape. Forex fluctuations have a significant impact on the everyday lives of both government agencies and the public population, directly influencing a country's prosperity or misfortune. This work proposes an advanced fuzzy time series model that incorporates domain universe sub-partitioning, parameter adjustment optimization methodologies, and interval forecasting methods. We utilized this model to examine annual exchange rate patterns between the Pakistani rupee (PKR) and the US dollar (US$), comparing its forecast accuracy to that of other models. Our proposed methodology outperformed existing methodologies in terms of forecasting precision, providing stakeholders with valuable insights for making informed, data-driven business decisions that benefit both individual firms and the country overall.</description><subject>American dollar</subject><subject>Astronomical models</subject><subject>Autoregressive integrated moving average</subject><subject>Average forecast error rate</subject><subject>Big Data</subject><subject>Central banks</subject><subject>Communications Engineering</subject><subject>Computational Science and Engineering</subject><subject>Computer Science</subject><subject>Currency</subject><subject>Data Mining and Knowledge Discovery</subject><subject>Database Management</subject><subject>Decision making</subject><subject>Economic development</subject><subject>Economic growth</subject><subject>Economic statistics</subject><subject>Forecasting</subject><subject>Forecasting techniques</subject><subject>Foreign exchange markets</subject><subject>Foreign exchange rates</subject><subject>Forex</subject><subject>Fuzzy sets</subject><subject>Fuzzy time series</subject><subject>Global economy</subject><subject>Information Storage and Retrieval</subject><subject>International trade</subject><subject>Mathematical Applications in Computer Science</subject><subject>Networks</subject><subject>Parameter modification</subject><subject>Set theory</subject><subject>Time series</subject><subject>Trends</subject><issn>2196-1115</issn><issn>2196-1115</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>ALSLI</sourceid><sourceid>COVID</sourceid><sourceid>M0C</sourceid><sourceid>M2R</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kU1v1DAQhiPUSlSlf4CTJc6hM7ETO9xQxUelIi70bE3i8eJlEy-2t7D99aQbBJw4WGONnue1pbeqXiK8RjTddVbQSl1Do2pAAFnrZ9VFg31XI2J79s_9eXWV8xYAUC5Opy6q8IkLTTHtv8Yc5o3wMfHPN4LcA80jTzyXLMIsHuKOStiFcjwRI-XyRB9ODokpuuADO-EPj49HUcLEInMKnIVPNPGPmL69qM497TJf_Z6X1f37d19uPtZ3nz_c3ry9q0cp-1J75MYPYDSNSi7H9Frj4GTve5aGyfcDaj96h6pxDA6M7LzqWLkWpVMgL6vbNddF2tp9ChOlo40U7GkR08ZSKmHcsfWDMcPgBmjbUXlvhs4RI7hedSRNS0vWqzVrn-L3A-dit_GQ5uX7ViJ2ujUa-oVqVmpMMefE_s-rCPapIbs2ZJeG7KkhqxdJrlJe4HnD6W_0f6xfQ3SWKg</recordid><startdate>20241015</startdate><enddate>20241015</enddate><creator>Bilal, Muhammad</creator><creator>Aamir, Muhammad</creator><creator>Abdullah, Saleem</creator><creator>Norrulashikin, Siti Mariam</creator><creator>Alqasem, Ohud A.</creator><creator>Elwahab, Maysaa E. A.</creator><creator>Khan, Ilyas</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><general>SpringerOpen</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88J</scope><scope>8AL</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>M0C</scope><scope>M0N</scope><scope>M2R</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>DOA</scope></search><sort><creationdate>20241015</creationdate><title>Metamorphosing forex: advancements in volatility forecasting using a modified fuzzy time series framework</title><author>Bilal, Muhammad ; Aamir, Muhammad ; Abdullah, Saleem ; Norrulashikin, Siti Mariam ; Alqasem, Ohud A. ; Elwahab, Maysaa E. A. ; Khan, Ilyas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c339t-f1e2fb087ac43ac489771bd39f9e38eaf9b17fcfd142de0d0836f46e4d513d403</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>American dollar</topic><topic>Astronomical models</topic><topic>Autoregressive integrated moving average</topic><topic>Average forecast error rate</topic><topic>Big Data</topic><topic>Central banks</topic><topic>Communications Engineering</topic><topic>Computational Science and Engineering</topic><topic>Computer Science</topic><topic>Currency</topic><topic>Data Mining and Knowledge Discovery</topic><topic>Database Management</topic><topic>Decision making</topic><topic>Economic development</topic><topic>Economic growth</topic><topic>Economic statistics</topic><topic>Forecasting</topic><topic>Forecasting techniques</topic><topic>Foreign exchange markets</topic><topic>Foreign exchange rates</topic><topic>Forex</topic><topic>Fuzzy sets</topic><topic>Fuzzy time series</topic><topic>Global economy</topic><topic>Information Storage and Retrieval</topic><topic>International trade</topic><topic>Mathematical Applications in Computer Science</topic><topic>Networks</topic><topic>Parameter modification</topic><topic>Set theory</topic><topic>Time series</topic><topic>Trends</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bilal, Muhammad</creatorcontrib><creatorcontrib>Aamir, Muhammad</creatorcontrib><creatorcontrib>Abdullah, Saleem</creatorcontrib><creatorcontrib>Norrulashikin, Siti Mariam</creatorcontrib><creatorcontrib>Alqasem, Ohud A.</creatorcontrib><creatorcontrib>Elwahab, Maysaa E. A.</creatorcontrib><creatorcontrib>Khan, Ilyas</creatorcontrib><collection>Springer Open Access</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection【Remote access available】</collection><collection>ProQuest Central (Corporate)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection</collection><collection>Social Science Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM global</collection><collection>Computing Database</collection><collection>Social Science Database</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Journal of big data</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bilal, Muhammad</au><au>Aamir, Muhammad</au><au>Abdullah, Saleem</au><au>Norrulashikin, Siti Mariam</au><au>Alqasem, Ohud A.</au><au>Elwahab, Maysaa E. A.</au><au>Khan, Ilyas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Metamorphosing forex: advancements in volatility forecasting using a modified fuzzy time series framework</atitle><jtitle>Journal of big data</jtitle><stitle>J Big Data</stitle><date>2024-10-15</date><risdate>2024</risdate><volume>11</volume><issue>1</issue><spage>143</spage><epage>16</epage><pages>143-16</pages><artnum>143</artnum><issn>2196-1115</issn><eissn>2196-1115</eissn><abstract>The interplay of exchange rates among nations significantly influences both international and domestic trade, underscoring the pivotal role of the foreign exchange market (Forex) in a country's economic landscape. Forex fluctuations have a significant impact on the everyday lives of both government agencies and the public population, directly influencing a country's prosperity or misfortune. This work proposes an advanced fuzzy time series model that incorporates domain universe sub-partitioning, parameter adjustment optimization methodologies, and interval forecasting methods. We utilized this model to examine annual exchange rate patterns between the Pakistani rupee (PKR) and the US dollar (US$), comparing its forecast accuracy to that of other models. Our proposed methodology outperformed existing methodologies in terms of forecasting precision, providing stakeholders with valuable insights for making informed, data-driven business decisions that benefit both individual firms and the country overall.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1186/s40537-024-01003-7</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2196-1115 |
| ispartof | Journal of big data, 2024-10, Vol.11 (1), p.143-16, Article 143 |
| issn | 2196-1115 2196-1115 |
| language | eng |
| recordid | cdi_doaj_primary_oai_doaj_org_article_fb88bbdb055c4ff8b6dae10d946a385a |
| source | ABI/INFORM global; Publicly Available Content Database; Springer Nature - SpringerLink Journals - Fully Open Access ; Social Science Premium Collection (Proquest) (PQ_SDU_P3); Coronavirus Research Database |
| subjects | American dollar Astronomical models Autoregressive integrated moving average Average forecast error rate Big Data Central banks Communications Engineering Computational Science and Engineering Computer Science Currency Data Mining and Knowledge Discovery Database Management Decision making Economic development Economic growth Economic statistics Forecasting Forecasting techniques Foreign exchange markets Foreign exchange rates Forex Fuzzy sets Fuzzy time series Global economy Information Storage and Retrieval International trade Mathematical Applications in Computer Science Networks Parameter modification Set theory Time series Trends |
| title | Metamorphosing forex: advancements in volatility forecasting using a modified fuzzy time series framework |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-24T17%3A14%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Metamorphosing%20forex:%20advancements%20in%20volatility%20forecasting%20using%20a%20modified%20fuzzy%20time%20series%20framework&rft.jtitle=Journal%20of%20big%20data&rft.au=Bilal,%20Muhammad&rft.date=2024-10-15&rft.volume=11&rft.issue=1&rft.spage=143&rft.epage=16&rft.pages=143-16&rft.artnum=143&rft.issn=2196-1115&rft.eissn=2196-1115&rft_id=info:doi/10.1186/s40537-024-01003-7&rft_dat=%3Cproquest_doaj_%3E3116758709%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c339t-f1e2fb087ac43ac489771bd39f9e38eaf9b17fcfd142de0d0836f46e4d513d403%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=3116758709&rft_id=info:pmid/&rfr_iscdi=true |