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Big Data, Artificial Intelligence, and Financial Economics
Organized by Itay Goldstein, Chester S. Spatt, Mao Ye, and Tarun Ramadorai Supported by the Office of Financial Research through an interagency agreement with the National Science Foundation December 13, 2024 Royal Sonesta Hotel, Parkview, 40 Edwin H. Land Blvd., Cambridge, MA Format: 20 minutes for presentation, 15 minutes for discussants and 20 minutes for general discussions |
Friday, December 13 | |
8:00am |
Continental Breakfast
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8:30am |
AI and Labor Market
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Income and Inequality under Asymptotically Full Automation
Discussant:
Winston Wei Dou, University of Pennsylvania and NBER |
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Big Data and Bigger Firms: A Labor Market Channel
Discussant:
Paul Goldsmith-Pinkham, Yale University and NBER |
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9:50am |
Break
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10:10am |
Measuring Economic Activities Using AI
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Measuring Creative Destruction
Discussant:
Maxime Bonelli, London Business School |
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Uncovering Information: Can Language Models Tell Us Where to Look?
Discussant:
Tim Loughran, University of Notre Dame |
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11:30am |
What Hundreds of Economic News Events Say About Belief Overreaction in the Stock Market
Discussant:
Francesca Bastianello, University of Chicago |
12:10pm |
Lunch
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1:30pm |
AI, Algorithm, and Retail Trading
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Navigating the Murky World of Hidden Liquidity
Discussant:
Thomas Ernst, University of Maryland, College Park |
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Retail Limit Orders
Discussant:
Joel Hasbrouck, New York University |
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2:50pm |
Break
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3:10pm |
Designing Artificial Homo Economicus
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Do Mutual Funds Benefit from the Adoption of AI Technology?
Discussant:
Simona Abis, University of Colorado Boulder |
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Teaching Economics to the Machines
Discussant:
Andrew Patton, Duke University |
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4:30pm |
Adjourn
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