Annual Conference

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Tech, Digital Markets and AI

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May 2025

Venture Capital Response to Government-Funded Basic Science

Roham REZAEI, Yufeng YAO
Science-based R&D can deter venture capitalists due to high technical uncertainty. We study whether mission-oriented public funding—supplying basic science as a public good—fosters VC investment. Our quasi-natural experiment is the BRAIN Initiative (BI), a large-scale government program aime...
Keywords: Venture Capital, innovation, academic entrepreneurship, government policy, machine learning
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Annual Conference

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Tech, Digital Markets and AI

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May 2025

Generative AI and Asset Management

Jinfei SHENG, Zheng SUN, Baozhong YANG, Alan ZHANG
This paper proposes a novel measure of investment companies’ reliance on generative AI, focusing on its implications for hedge funds. We document a sharp increase in generative AI usage by hedge funds after ChatGPT’s 2022 launch. A difference-in-differences test shows that hedge funds adopting g...
Keywords: Generative AI (GenAI), ChatGPT, Hedge Funds, GenAI Reliance, Portfolio Return, Alpha, Survey, AI Disparity
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Annual Conference

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Tech, Digital Markets and AI

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May 2025

Disciplining Banks through Disclosure: Evidence from CFPB Consumer Complaints

Jeffrey JOU, Anya KLEYMENOVA, Andrea PASSALACQUA, Laszlo SANDOR, Rajesh VIJAYARAGHAVAN
We study the depositors’ reaction to the disclosure of consumer complaints about their banks. Using the Consumer Financial Protection Bureau (CFPB) complaints data, we find banks subject to prudential CFPB oversight that receive consumer complaints experience a decline in uninsured deposits and re...
Keywords: Disclosure, CFPB, Consumer complaints, AI, LLM, ChatGPT
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Annual Conference

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Tech, Digital Markets and AI

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May 2025

Firm-Level Input Price Changes and Their Effects: A Deep Learning Approach

Sudheer CHAVA, Wendi DU, Indrajit MITRA, Andrea LU, Agam SHAH
We develop firm-level measures of input and output price changes based on textual analysis of earnings calls. Our measures establish five facts: (1) The median firm experiences an increase (decrease) in input prices every 7 (30) months. (2) Input price changes are driven by aggregate and firm specif...
Keywords: Input price changes, pass through, Earnings conference calls, deep learning, stock returns
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Annual Conference

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Tech, Digital Markets and AI

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May 2025

Centralized Governance in Decentralized Organizations

Lin William CONG, Daniel RABETTI, Charles C.Y. WANG, Yu YAN
We systematically document governance centralization in decentralized autonomous organizations (DAOs) and study its drivers and economic implications. Using multiple data sources and granular on-chain transactional data, we compare our findings to those in corporate finance (and venture startup) set...
Keywords: Blockchain, Blockholder Activism, DAOs, DeFi Ventures, Governance, Insider Trading, Voting
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