Sean Cao Wins Two Best Paper Awards for AI Research

Smith associate professor Sean Cao, director and co-founder of the Smith AI Initiative for Capital Market Research, recently received two best paper awards for his research on using artificial intelligence in capital markets. Cao is a leading researcher in how humans can work with AI-powered machines — “instead of being replaced by them,” he says.

Cao won the FAMA-DFA Prize from the Journal of Financial Economics for his paper, “From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses.” In the paper, Cao and his co-authors looked at how AI is changing the job for stock analysts and how AI analysts stack up against their human counterparts. They found that AI was clearly better at processing large volumes of data from public information, but humans outperformed AI when judgement and institutional knowledge are part of the equation. The best performance, with the highest forecast accuracy and the fewest errors, comes when combining human judgement with AI tools. “The biggest takeaway from the research is just how strong the outcome can be when people work with AI,” Cao says. (Read ‘Why Man + Machine Adds Up to Better Stock Picks’)

Each year, Journal of Financial Economics subscribers vote for the best paper in each of two categories after the journal's editorial office has enumerated all articles and assigned them to the corporate finance and asset pricing areas. The award is named after influential economist Eugene Fama, a 2013 Nobel laureate in economics and co-founding advisory editor of the journal. The prize is also named for investment advisory firm Dimensional Fund Advisors, where Fama is a research director.
 
Cao also won the Michael J. Brennan Award from The Review of Financial Studies for “How to Talk When Machines Are Listening: Corporate Disclosure in the Age of AI.” The paper examines how corporate managers produce information when that information is primarily consumed by machine traders rather than human traders. The findings show that firms facing greater AI readership make their disclosures more machine-readable and strategically manage language and tone to account for how algorithms process the information. That affects how quickly that information impacts stock prices, highlighting what happens in the market when AI analyzes corporate communications.

Taken together, these studies provide a unified view of human-AI interaction in capital markets, showing how advances in artificial intelligence not only change how information is analyzed by investors but also how information is produced and communicated by firms.

Both award-winning papers have also attracted attention from major media outlets, including the Financial Times, CNBC, Bloomberg, The Guardian, Quartz, and IR Magazine.