A bibliometric analysis on the application of deep learning in economics, econometrics, and finance
by Arash Salehpour; Karim Samadzamini
International Journal of Computational Science and Engineering (IJCSE), Vol. 27, No. 2, 2024

Abstract: This research looked at the deep learning applications in economics, econometrics, and finance. Two hundred fifty articles from the Scopus database's index of journals published between 2013 and 2022 were gathered using a bibliometric technique. The data was analysed using many programs (R studio, Excel, and Biblioshiny), and in terms of countries, organisations, publications, papers, and authors, the most prominent scientific players were highlighted. Our research found that as of 2019, the quantity of publications has increased. The literature analysis received the most contributions from China and the USA. The most significant findings and discussions came from the following analyses: estimation of share prices, asset management price fluctuations and liquidity, forecast of bankruptcies, evaluation of credit risk, risk assessment, commodity prices top trend analysis, citation analysis, thematic evolution, and thematic map. Our findings offer practical recommendations on how deep learning may be implemented into decision-making processes for market participants, particularly those working in fintech and finance.

Online publication date: Mon, 11-Mar-2024

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com