Analysis of CBDC Narrative OF Central Banks using Large Language Models
Author
Abstract
Suggested Citation
DOI: https://doi.org/10.53479/33412
Download full text from publisher
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Can Celebi & Stefan Penczynski, 2024. "Using Large Language Models for Text Classification in Experimental Economics," Working Paper series, University of East Anglia, Centre for Behavioural and Experimental Social Science (CBESS) 24-01, School of Economics, University of East Anglia, Norwich, UK..
- Chong Zhang & Xinyi Liu & Zhongmou Zhang & Mingyu Jin & Lingyao Li & Zhenting Wang & Wenyue Hua & Dong Shu & Suiyuan Zhu & Xiaobo Jin & Sujian Li & Mengnan Du & Yongfeng Zhang, 2024. "When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments," Papers 2407.18957, arXiv.org, revised Sep 2024.
- Wu, WenTing & Chen, XiaoQian & Zvarych, Roman & Huang, WeiLun, 2024. "The Stackelberg duel between Central Bank Digital Currencies and private payment titans in China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
More about this item
Keywords
ChatGPT; BERT; CBDC; digital money;All these keywords.
JEL classification:
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
- G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
- E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
NEP fields
This paper has been announced in the following NEP Reports:- NEP-AIN-2023-09-25 (Artificial Intelligence)
- NEP-BAN-2023-09-25 (Banking)
- NEP-BIG-2023-09-25 (Big Data)
- NEP-CBA-2023-09-25 (Central Banking)
- NEP-CMP-2023-09-25 (Computational Economics)
- NEP-MON-2023-09-25 (Monetary Economics)
- NEP-PAY-2023-09-25 (Payment Systems and Financial Technology)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bde:wpaper:2321. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ángel Rodríguez. Electronic Dissemination of Information Unit. Research Department. Banco de España (email available below). General contact details of provider: https://edirc.repec.org/data/bdegves.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.