Alejandro Lopez Lira (University of Florida): ChatGPT and Corporate Policies

The Stanford AFTLab invites you to the AI & Big Data in Finance Research Forum (ABFR) webinar:

The webinar is on May 29, 9-10am Pacific Time (12-1pm ET)

Presenter: Michael Weber (Chicago Booth) 

Discussant: Alejandro Lopez Lira (University of Florida) 

Zoom webinar link: https://stanford.zoom.us/j/91354916559?pwd=Eval1lG0bFUSbDdI8NXDaDZ09CRI6i.1

Meeting ID: 913 5491 6559

Passcode: 231587

For more information, please visit our website: https://www.abfr-forum.org

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Title: ChatGPT and Corporate Policies 

Authors: Manish Jha (Georgia State University), Jialin Qian (Georgia State University), Michael Weber (University of Chicago) and Baozhong Yang (Georgia State University)

Abstract: We create a firm-level ChatGPT investment score, based on conference calls, that measures managers’ anticipated changes in capital expenditures. We validate the score with interpretable textual content and its strong correlation with CFO survey responses. The investment score predicts future capital expenditure for up to nine quarters, controlling for Tobin’s q and other determinants, implying the investment score provides incremental information about firms’ future investment opportunities. Consistent with theoretical predictions, high-investment-score firms experience significant positive short-term returns upon disclosure, and negative long-run future abnormal returns. We demonstrate ChatGPT’s applicability to measure other policies, such as dividends and employment. 

Bio of speaker: Michael Weber joined Chicago Booth in 2014 as an Assistant Professor of Finance and was promoted to Associate Professor in 2018. He is also a faculty research fellow at the National Bureau of Economic Research in the Monetary Economics and Asset Pricing groups, a member of the Macro Finance Society, and a research affiliate at the CESifo Research Network. His research interests include asset pricing, macroeconomics, international finance, and household finance. His work on downside risk in currency markets and other asset classes earned the 2013 AQR Insight Award. He has published in leading economics and finance journals such as the American Economic Review, the Review of Economic Studies, and the Journal of Financial Economics. Weber is a visiting researcher at the Bureau of Labor Statistics where he studies how the inability of firms to adjust output prices to macroeconomics shocks affects their systematic risk. Weber frequently presents his research at major international conferences such as the American Economic Association or the NBER Summer Institute. His research was covered by The Economist, Die Welt, La Stampa, Haaretz, among others.His research was awarded the 2017 Chakoozian Endowed Risk Management Prize, 2016 ECB Lamfalussy Research Fellowship, 2016 Center for Financial Research Best Paper Award, the Top Finance Graduate Award 2014, the WFA Cubist Systematic Strategies PhD Award for Outstanding Research, the UBS Best Conference Paper Prize at the EFA Annual Meeting 2014, the 2014 EFA Best Doctoral Student Conference Paper Prize, the Best Finance PhD Award in Honor of Prof. Greenbaum 2013 (Finalist), and the Best PhD Student Paper Award, FMA European Conference 2014. Weber earned a Ph.D. and an M.S. both in Finance from the Haas School of Business at the University of California, Berkeley. Prior to his doctoral studies, he has worked in the debt advisory division of Rothschild, the Corporate Finance (M&A) advisory at KPMG, and the finance division of the Centre for European Economic Research (ZEW). He also holds a Diplom in Business Economics (with distinction) from the University of Mannheim which earned him the SEW Eurodrive dissertation award.

Bio of discussant: Alejandro Lopez-Lira is an Assistant professor of Finance at Warrington College of Business, University of Florida. He holds a PhD in Finance from the Wharton School, University of Pennsylvania. His research covers topics in Empirical Asset Pricing, Machine Learning and Textual Analysis. He is the author of the forthcoming book "The Predictive Edge: Outsmart the Market Using Generative AI and ChatGPT in Financial Forecasting", which provides readers with innovative strategies for leveraging large language models like ChatGPT to uncover opportunities in the stock market. The book has already received acclaim, leading to Lopez-Lira being awarded the prestigious 2023 BlackRock Best Paper Prize for the underlying research.