Alex G. Kim

University of Chicago Booth School of Business
Ph.D. Candidate in Accounting

👋 Hi! I'm Alex Kim.

I'm a Ph.D. candidate in accounting at the University of Chicago, Booth School of Business. I received a Master's degree in Business Administration with a concentration in Accounting and a dual Bachelor's degree in Economics and Business Administration, Summa Cum Laude, from Seoul National University. I passed the Korean CPA exam in 2018.

My research mainly examines the information processing of investors in the capital market. Recently, I have been interested in studying how large language models and artificial intelligence (AI) can assist investors in processing information and making economic decisions. My research has been featured in major media outlets such as the Financial Times, Bloomberg, Fortune, and Forbes and accepted for publication in prestigious academic journals such as the Journal of Accounting Research and the Journal of Accounting and Economics. My research has been funded by the Ernest R. Wish Ph.D. Research Fellowship, the Stevens Doctoral Program, and the Fama-Miller Center for Finance Research. This article from Chicago Booth Review collectively discusses my works in generative LLMs, AI, and financial accounting.

Contact: alex.kim@chicagobooth.edu
Academic Profile: SSRN, arXiv, Google Scholar

December 2024. [New Paper] "Learning Fundamentals from Text" is now available on SSRN.
November 2024. "Vocal Delivery Quality in Earnings Conference Calls" is forthcoming in the Journal of Accounting and Economics.
October 2024. "Context-Based Interpretation of Financial Information" is forthcoming in the Journal of Accounting Research.

October 2024. "Bloated Disclosures: Can ChatGPT Help Investors Process Information" received the 2024 FMA Annual Conference Best Paper Award in Corporate Finance.
July 2024. "From Transcripts to Insights: Uncovering Corporate Risks Using Generative AI" received the 2024 FMA Asia-Pacific Conference Best Paper Award in Corporate Finance.
June 2024. "From Transcripts to Insights: Uncovering Corporate Risks Using Generative AI" received the 2024 FMA Applied Finance Conference Best Paper Award.
May 2024. "Bloated Disclosures: Can ChatGPT Help Investors Process Information" received the 2024 FARS Midyear Best Paper Award.
May 2024. [New Paper] "Financial Statement Analysis with Large Language Models" is now available on SSRN.
May 2024. [New Paper] "DEBATE: Devil's Advocate Based Assessment and Text Evaluation" has been accepted for publication at the 2024 ACL. The paper is now available on SSRN, arXiv, and ACL Anthology.
May 2024. [Companion App] Financial Statement Analyzer using GPTs by OpenAI is now available. See the Data tab for details.
November 2023. [New Paper] "Economic Footprints of Tax Audits: A Generative AI-Driven Approach" is now available on SSRN.
November2023. [Project Website] CompanyInsight.AI is now public. See the Data tab for details.
October 2023. [New Paper] "From Transcripts to Insights: Uncovering Corporate Risks Using Generative AI" is now available on SSRN and arXiv.
May 2023. [New Paper] "Profitability Context and the Cross-Section of Stock Returns" is now available on SSRN.
April 2023. [New Paper] "Bloated Disclosures: Does ChatGPT Help Investors Process Financial Information?" is now available on SSRN and arXiv.
March 2023. [New Paper] "Managers' Vocal Delivery and Real-Time Market Reactions in Earnings Calls" is now available on SSRN.
January 2023. [New Paper] "Context-Based Interpretation of Financial Information" is now available on SSRN.

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