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001-es BibID:	BIBFORM125425
Első szerző:	Chowdhury, Rubaiyat Shaimom
Cím:	Implications of Artificial Intelligence (AI) and machine learning-based fintech for the financial assets related traditional investment theories / Rubaiyat Shaimom Chowdhury, Aminul Islam, Dayang Hasliza Binti Muhd Yusuf, Mohammad Bin Amin, Sharif Hassan, Suborna Barua, Masuk Abdullah
Dátum:	2024
ISSN:	2572-7923 2572-7931
Megjegyzések:	New technologies always have an impact on traditional theories. Finance theories are no exception to that. In this paper, we have concentrated on the traditional investment theories in finance. The study examined five investment theories, their assumptions, and their limitation from different works of literature. The study considered Artificial Intelligence (AI) and Machine Learning (ML) as representative of financial technology (fintech) and tried to find out from the literature how these new technologies help to reduce the limitations of traditional theories. We have found that fintech does not have an equal impact on every conventional finance theory. Fintech outperforms all five traditional theories but on a different scale.
Tárgyszavak:	Társadalomtudományok Gazdálkodás- és szervezéstudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk artificial intelligence machine learning fintech traditional investment theories financial assets
Megjelenés:	Journal of Infrastructure Policy and Development. - 8 : 12 (2024), p. 1-19. -
További szerzők:	Islam, Aminul Yusuf, Dayang Hasliza Binti Muhd Mohammad, Bin Amin (1981-) (PhD student) Hassan, Sharif Barua, Suborna Masuk, Abdullah (1997-) (mechatronics)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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