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Artificial intelligence and machine learning in finance: A bibliometric review · Study

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ArticleArtificial intelligence and machine learning in finance: A bibliometric review

Shamima Ahmed2022

Article2022

Artificial intelligence and machine learning in finance: A bibliometric review

Shamima Ahmed · Muneer Maher Alshater · Anis El Ammari · Helmi Hammami

468 citations·0/0 files stored·Research in International Business and Finance

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Stock Market Forecasting Methods Artificial Intelligence Applications FinTech, Crowdfunding, Digital Finance

Abstract

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Citations in this library

Stored only when both papers are in the corpus — 468 citations exist upstream.

References

2009Software survey: VOSviewer, a computer program for bibliometric mapping 2017bibliometrix : An R-tool for comprehensive science mapping analysis 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 2021How to conduct a bibliometric analysis: An overview and guidelines 1974ON THE PRICING OF CORPORATE DEBT: THE RISK STRUCTURE OF INTEREST RATES*1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 1969Statistical bibliography or bibliometrics 1977ZETATM analysis A new model to identify bankruptcy risk of corporations

Cited by

2023State-of-the-Art of Artificial Intelligence and Big Data Analytics Reviews in Five Different Domains: A Bibliometric Summary 2023Machine learning sentiment analysis, COVID-19 news and stock market reactions 2023Islamic Finance in the Era of Financial Technology: A Bibliometric Review of Future Trends 2025FinTech: a literature review of emerging financial technologies and applications 2025Artificial intelligence in the renewable energy transition: The critical role of financial development 2022Artificial intelligence adoption in the insurance industry: Evidence using the technology–organization–environment framework 2022Digital economy and business investment efficiency: Inhibiting or facilitating?2025AI integration in financial services: a systematic review of trends and regulatory challenges

Details

Year2022

Typearticle

Published2022-04-04

VenueResearch in International Business and Finance

ISSN-L0275-5319

Languageen

Citations468

Files0 public / 0

ShelfStock Market Forecasting Methods

Identifiers

doi10.1016/j.ribaf.2022.101646

openalex_workW4224037372

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