https://m2.mtmt.hu/ hun 2026-06-27 14:56 JournalArticle 36948192 APPROVED true 0 false 2026-04-13T06:54:32.272+0000 2026-04-13T06:53:25.621+0000 2026-02-16T08:12:16.082+0000 true 10015147 Lengyel Péter /api/author/10015147 Author Lengyel Péter (Gazdálkodás- és szervezéstudományok) true 10015147 2026-04-13T06:53:25.776+0000 2026-04-13T06:53:25.776+0000 true false true 24 24 /api/publicationtype/24 PublicationType Folyóiratcikk 1 true 24 JournalArticle true 10000059 Article true 24 24 /api/publicationtype/24 PublicationType Folyóiratcikk 1 true 24 JournalArticle /api/subtype/10000059 Szakcikk SubType Szakcikk (Folyóiratcikk) 101 true 10000059 true 1 /api/category/1 Category Tudományos true 1 Lengyel, Péter true 20101147 false true /api/journal/20101147 2731-0809 REVIEWED Journal Discover Artificial Intelligence 2731-0809 true false false 6 1 217 217 20 2026 This review synthesises research on fintech implications of integrating machine learning algorithms into cryptocurrency trading strategies to address the fragmented understanding of their impact on trading efficacy, risk management, and financial innovation. The review aimed to evaluate current knowledge on machine learning applications, benchmark algorithmic trading performance, identify risk mitigation techniques, compare algorithm effectiveness, and examine regulatory and ethical considerations. A systematic analysis of diverse methodologies, including supervised, reinforcement, and hybrid learning models across global computational finance and AI literature, was conducted. Findings indicate that deep learning and ensemble methods significantly enhance predictive accuracy and trading profitability under volatile market conditions, while reinforcement learning frameworks improve dynamic portfolio optimisation and risk-adjusted returns. Risk management benefits arise from integrating technical indicators and reward-based safety mechanisms, though universal frameworks remain lacking. Fintech integration advances through blockchain-enabled transparency and automation, yet practical deployment faces scalability and interoperability challenges. Ethical and regulatory discourse is nascent, underscoring the need for responsible AI frameworks to ensure market integrity and investor protection. These findings collectively demonstrate that machine learning substantially transforms cryptocurrency trading strategies, offering enhanced performance and risk control within evolving fintech infrastructures, while highlighting critical gaps in regulatory compliance and ethical governance that warrant focused future research. true 2026 true true true false true false NONE 2026-04-13 false 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Q1 false false false false 2026-05-17T07:12:16.667+0000 Módszertani és Üzleti Digitalizáció Intézet (DE / GTK) 3 11 1 3 0 false Language 10002 /api/language/10002 Angol Angol English true 2 true PersonAuthorship 133982220 /api/authorship/133982220 Lengyel, Péter [Lengyel, Péter (Gazdálkodás- és s...), szerző] Módszertani és Üzleti Digitalizáció Intézet (DE / GTK) 1 0.333 true false false Author 10015147 /api/author/10015147 Lengyel Péter (Gazdálkodás- és szervezéstudományok) Lengyel Péter true 10015147 true Lengyel Péter true false false AuthorshipType 1 /api/authorshiptype/1 Szerző 0 true 0 true false true PersonAuthorship 133982221 /api/authorship/133982221 Pancsira, János [Pancsira, János (gazdálkodás- és s...), szerző] Módszertani és Üzleti Digitalizáció Intézet (DE / GTK) 2 0.333 false false false Author 10049005 /api/author/10049005 Pancsira János (gazdálkodás- és szervezéstudományok) Pancsira János true 10049005 true Pancsira János true false false AuthorshipType 1 /api/authorshiptype/1 Szerző 0 true 0 true false true PersonAuthorship 133982222 /api/authorship/133982222 Füzesi, István [Füzesi, István (Gazdálkodás- és s...), szerző] Módszertani és Üzleti Digitalizáció Intézet (DE / GTK) 3 0.333 false true false Author 10015348 /api/author/10015348 Füzesi István (Gazdálkodás- és szervezéstudományok) Füzesi István true 10015348 true Füzesi István true false false AuthorshipType 1 /api/authorshiptype/1 Szerző 0 true 0 true false true PublicationIdentifier 31434475 /api/publicationidentifier/31434475 DOI: 10.1007/s44163-025-00785-w PlainSource 6 /api/publicationsource/6 DOI PublicationSourceType 10001 /api/publicationsourcetype/10001 DOI true true true DOI DOI https://doi.org/@@@ true true 6 true IDENTICAL 10.1007/s44163-025-00785-w https://doi.org/10.1007/s44163-025-00785-w false true PublicationIdentifier 31823907 /api/publicationidentifier/31823907 Scopus: 105033702589 PlainSource 3 /api/publicationsource/3 Scopus PublicationSourceType 10003 /api/publicationsourcetype/10003 Indexelő adatbázis false true true Scopus Scopus http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-@@@ true true 3 true IDENTICAL 105033702589 http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-105033702589 false true PublicationIdentifier 31434476 /api/publicationidentifier/31434476 Egyéb URL: https://link.springer.com/10.1007/s44163-025-00785-w PlainSource 40 /api/publicationsource/40 Egyéb URL PublicationSourceType 10006 /api/publicationsourcetype/10006 Link true true true Egyéb URL Other URL @@@ true true 40 true https://link.springer.com/10.1007/s44163-025-00785-w https://link.springer.com/10.1007/s44163-025-00785-w false true SjrRating 11679241 /api/sjrrating/11679241 sjr:Q1 (2026) Scopus - Computer Vision and Pattern Recognition Discover Artificial Intelligence 2731-0809 21 0.24 journal RatingType 10002 /api/ratingtype/10002 sjr sjr true true ClassificationExternal 1707 /api/classificationexternal/1707 Scopus - Computer Vision and Pattern Recognition true 1707 true Q1 FROM_PREVIOUS_TO_LAST_YEAR true true Reference 72469358 /api/reference/72469358 1. 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(2026) Discover Artificial Intelligence 2731-0809 6 1<div class="JournalArticle Publication long-list"> <div class="authors"> <img title="Forrásközlemény" style="float: left" src="/frontend/resources/grid/publication-core-icon.png"> <div class="autype autype0"> <span class="author-name" mtid="10015147"><a href="/gui2/?type=authors&mode=browse&sel=10015147" target="_blank">Lengyel Péter (<span class="authorship-author-name">Lengyel Péter</span> <span class="authorAux-mtmt"> Gazdálkodás- és szervezéstudományok</span>) </a> </span> <span class="author-affil"><span title="Debreceni Egyetem">DE</span>/<span title="Gazdaságtudományi Kar">GTK</span>/Módszertani és Üzleti Digitalizáció Intézet</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10049005"><a href="/gui2/?type=authors&mode=browse&sel=10049005" target="_blank">Pancsira János (<span class="authorship-author-name">Pancsira János</span> <span class="authorAux-mtmt"> gazdálkodás- és szervezéstudományok</span>) </a> </span> <span class="author-affil"><span title="Debreceni Egyetem">DE</span>/<span title="Gazdaságtudományi Kar">GTK</span>/Módszertani és Üzleti Digitalizáció Intézet</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10015348"><a href="/gui2/?type=authors&mode=browse&sel=10015348" target="_blank">Füzesi István (<span class="authorship-author-name">Füzesi István</span> <span class="authorAux-mtmt"> Gazdálkodás- és szervezéstudományok</span>) </a> </span> <span class="author-affil"><span title="Debreceni Egyetem">DE</span>/<span title="Gazdaságtudományi Kar">GTK</span>/Módszertani és Üzleti Digitalizáció Intézet</span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;36948192" target="_blank">Machine learning integration in cryptocurrency trading and its fintech implications</a></div> <div> <span class="journal-title">Discover Artificial Intelligence</span> <span class="journal-issn">( <a target="_blank" href="https://portal.issn.org/resource/ISSN/2731-0809">2731-0809</a>)</span>: <span class="journal-volume">6</span> <span class="journal-issue">1</span> <span class="page"> Paper 217. 20 p. </span> <span class="year">(2026)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Nyelv: Angol | </span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="10.1007/s44163-025-00785-w" target="_blank" href="https://doi.org/10.1007/s44163-025-00785-w"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="105033702589" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-105033702589"> Scopus </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:black" title="https://link.springer.com/10.1007/s44163-025-00785-w" target="_blank" href="https://link.springer.com/10.1007/s44163-025-00785-w"> Egyéb URL </a> </span> </span> <OnlyViewableByAuthor><div class="ratings"> <div class="journal-subject">Folyóirat szakterülete: Scopus - Artificial Intelligence&nbsp;&nbsp;&nbsp;SJR indikátor:&nbsp;Q1</div> <div class="journal-subject">Folyóirat szakterülete: Scopus - Computer Vision and Pattern Recognition&nbsp;&nbsp;&nbsp;SJR indikátor:&nbsp;Q1</div> <div class="journal-subject">Folyóirat szakterülete: Scopus - Human-Computer Interaction&nbsp;&nbsp;&nbsp;SJR indikátor:&nbsp;Q1</div> <div class="journal-subject">Folyóirat szakterülete: Scopus - Information Systems&nbsp;&nbsp;&nbsp;SJR indikátor:&nbsp;Q1</div> </div></OnlyViewableByAuthor> <div class="mtid"><span class="long-pub-mtid">Közlemény: 36948192</span> | <span class="status-data status-APPROVED"> Nyilvános </span> Forrás | <span class="type-subtype">Folyóiratcikk ( Szakcikk ) </span> | <span class="pub-category">Tudományos</span> | <span class="publication-sourceOfData"></span> </div> <div class="lastModified">Utolsó módosítás: 2026.04.13. 08:53 Pergéné Szabó Enikő (admin) </div> </div></div>