The Fourth NBER-SAIF Research Conference, jointly organized by the National Bureau of Economic Research (NBER) and the Shanghai Advanced Institute of Finance (SAIF) at Shanghai Jiao Tong University, convened online on June 15th–16th, 2026 (US Eastern Time).
Under the theme “AI and Financial Markets,” the conference gathered finance and economics scholars from leading universities and research institutions worldwide for in-depth discussion of how artificial intelligence is reshaping financial markets, asset pricing, financial decision-making, labor inputs, innovation, and regulation.
This conference marked the fourth installment in the ten-year strategic partnership between NBER and SAIF, launched in 2018 to build a high-level platform for the international academic community and to foster rigorous research on critical issues in finance and macroeconomics.
In his opening remarks, NBER President and MIT Professor James Poterba emphasized that although the financial markets and macroeconomic mechanisms of China and the United States differ institutionally, many core questions carry cross-market, cross-national relevance — offering fertile ground for comparative research using common analytical tools.
Since its inception, the NBER-SAIF series has consistently addressed frontier topics of real-world and scholarly significance, with previous editions examining social security and public pensions, China's real estate market and housing finance, and climate finance and the sustainable energy transition. This year's focus on AI and financial markets responds to the new questions that rapid advances in AI pose for financial research, market practice, and public policy.
The conference received a record 281 paper submissions, from which ten were selected for presentation across four sessions: “Data, AI, and Markets,” “AI and Financial Decisions,” “AI and Labor Inputs,” and “Innovation, Regulation, and AI.” James Poterba and Professor Yongxiang Wang (SAIF Professor of Finance and Deputy Dean) opened the conference with joint remarks, and the four sessions were chaired respectively by Professor Feng Li (Chair Professor of Accounting and Deputy Dean of SAIF), Professor Laura Veldkamp (Columbia University, NBER), Professor Xiaoyun Yu (Chair Professor of Finance and Deputy Dean of SAIF), and Professor Viral Acharya (New York University, NBER).
In the first session, “Data, AI, and Markets,” Laura Veldkamp presented “The Missing Value of Data,” examining how the value of corporate data is measured and its role in market valuation, while Jincheng Tong presented “Data, Markups, and Asset Prices,” analyzing how firms use data to forecast demand and set prices — and how this, in turn, shapes markups and asset prices.
The second session, “AI and Financial Decisions,” focused on AI's effects on investment, pricing, and financial advice. Semyon Malamud discussed the theoretical and applied potential of AI methods in asset-pricing models; Yiwen Lu examined AI's impact on the tasks and behavior of financial professionals; and Jing Huang studied the frictions AI advisors face in processing soft information such as risk preferences and tax considerations.
The third session, “AI and Labor Inputs,” turned to the workplace. Christos A. Makridis presented large-scale longitudinal survey evidence on the diffusion and use of AI in the financial sector and its effects on employee behavior and organizational structure, while Miao Ben Zhang used internet browsing data to examine how generative AI affects household information acquisition, time allocation, and daily activities.
The final session, “Innovation, Regulation, and AI,” extended the discussion to firm productivity, entrepreneurship, and financial regulation. Zhaoxia Xu explored whether and how AI affects productivity through innovation channels; Bo Bian studied the impact of generative AI on entrepreneurial entry and behavior; and Antonio Coppola analyzed, from a macroprudential perspective, the new capabilities, boundaries, and risks that AI tools introduce to financial regulation.
Throughout the conference, scholars engaged in lively exchanges on AI's application boundaries, methodological innovations, and associated risks, broadening the research agenda for the field.
In his closing remarks, James Poterba identified several interconnected and rapidly evolving research directions to emerge from the conference: the valuation of AI and its impact on market prices, AI's transformation of financial decisions by firms, investors, and households, AI's effects on behavior and productivity, and AI's potential to reshape regulatory tools and capacity. He underscored the enduring value of the NBER-SAIF partnership and the importance of open global academic exchange in a complex international environment.
Yongxiang Wang thanked all presenters, authors, session chairs, participants, and organizers, and offered a cautionary note through the story of the Polish film “Dekalog 1”: however powerful its possibilities, AI should not be seen as a substitute for human judgment. As AI takes on an increasingly central role in financial markets, harnessing its efficiency and analytical power while maintaining prudence, transparency, and accountability will remain a critical challenge for academia, industry, and regulators alike.
The conference deepened the long-term academic collaboration between NBER and SAIF and laid the groundwork for continued cooperation among global scholars on AI and financial markets. Looking forward, the NBER-SAIF series will continue as an open, rigorous, and forward-looking platform for addressing key issues in global finance and economics.
