Review of Financial Studies

Cambridge, MA: December 13, 2024

The proliferation of large unstructured datasets along with advances in artificial intelligence (AI) technology provides researchers in financial economics with new opportunities for data analysis, and it also changes the set of subjects these researchers are studying. As AI becomes increasingly important in making decisions using financial market data, it becomes crucial to study how AI interacts with both data resources and with human decision-makers.

To promote research on emerging issues related to the methodology, applications, and socioeconomic implications of the growing availability of large datasets and AI tools, the National Bureau of Economic Research (NBER), with the generous support of the Office of Financial Research (OFR) and in collaboration with the Review of Financial Studies (RFS), will convene a research conference on December 13, 2024. The program will be organized by RFS Executive Editor Tarun Ramadorai of Imperial College London, and NBER Research Associates Itay Goldstein of the University of Pennsylvania, Chester Spatt of Carnegie Mellon University, and Mao Ye of Cornell University.

The organizers will consider submissions on topics including, but not limited to:

• Unstructured Data Analysis and AI: The impact on financial markets of the growing use of AI technology to analyze unstructured data, such as text, images, audio, and video.
• Trading and AI: The impact of using AI in high-frequency trading, algorithmic trading, and the impacts of this use on financial markets.
• Big Data and AI in Investment: The rise of machines in asset management, particularly the growing analysis of high-dimensional datasets using machine learning techniques.
• Big Data and AI in Corporate Decisions: The impact of AI as well as other means of analyzing unstructured datasets and automating decision making on corporate decisions, such as capital budgeting, working capital management, and regulatory compliance and reporting.
• Financial Institutions and Financial Intermediation: The impact of AI, fintech, and the analysis of large datasets on traditional financial institutions.
• AI and Regulation: The role of AI in detecting improper market conduct, the regulation of algorithms and winner-take-all markets, and strategies for ensuring accountability, fairness and transparency in AI models.

The organizers welcome submissions of both empirical and theoretical research papers and encourage submissions from scholars who are early in their careers, who are not NBER affiliates, and who are from under represented groups in the financial economics profession.

Papers that are submitted for presentation at the conference may also be submitted to the RFS under its dual review system at no extra cost. Papers that are rejected at any stage of this process are not considered to have been rejected the RFS.  Authors may submit a future version of the same paper to the RFS, even if the paper is not selected for presentation at the conference. For a paper to be considered under the dual submission option, it may not be under review or invited revision at any journal, including the RFS, until the author has been notified of the outcome of the dual submission process. The details of the dual submission program may be found at https://sfs.org/dualsubmissionpolicy.

To be considered for inclusion on the program, papers must be uploaded by 11:59 pm EDT on Thursday, September 12, 2024 to one of the following sites:

For submissions to both the conference and the Review of Financial Studies:

https://conference.nber.org/confsubmit/backend/cfp?id=BDSMf24r

For submissions to the conference alone:

https://conference.nber.org/confsubmit/backend/cfp?id=BDSMf24

Please do not submit papers that have been accepted for publication or that will be published before the conference.  Authors chosen to present papers will be notified in October, 2024.  All presenters are expected to attend the meeting in person. The NBER will cover the travel and lodging cost of up to two presenters per paper.

Questions about this conference may be addressed to gargera@nber.org.