Research
Job Market Paper
[1] Do Mandatory Disclosures Inform Criminals?: Corporate Transparency and Cybersecurity Risks
Committee Members: Eric So (co-chair), Rodrigo Verdi (co-chair), Nemit Shroff, and Andrew Sutherland
Presented at: MIT Accounting, MIT CAMS (Cybersecurity at MIT Sloan), WashU Olin Accounting Research Conference, KAAPA PhD Conference (Best Paper Award)
Abstract
I study whether disclosure mandates alter the equilibrium of cyberattacks by unintentionally informing cybercriminals. The California Consumer Privacy Act (CCPA) requires companies to disclose their personal information collection practices to consumers, inadvertently informing cybercriminals about the potential benefits of breaching each firm. Using a difference-in-differences design, I find that firms disclosing the collection of valuable personal data face an increased probability of data breaches. These firms also strengthen their cyberdefenses, both in terms of software and employee cybersecurity expertise. Firms trade off cybersecurity costs against the risk of data breaches, with the increase in breach probabilities more pronounced among firms that invest less in cybersecurity. Finally, I find that firms voluntarily disclose more about their cyberdefense and adjust their data-collection policies as additional defense strategies. Overall, this study highlights the trade-off between transparency and cybersecurity risks in today's economy.
Working Papers
[2] Vocal Delivery Quality in Earnings Conference Calls
Co-authors: Bok Baik (SNU), Alex Kim (U of Chicago), and Sangwon Yoon (non-academic)
Conditionally accepted at Journal of Accounting and Economics
Presented at: MIT, National University of Singapore, University of Chicago, Yonsei University, 2022 MIT Asia Accounting Conference, 2022 Korean Accounting Association Summer Conference, 2023 American Accounting Association Annual Meeting, 2023 S&P Quant Investing Conference
Press coverage: Columbia Law School Blue Sky Blog, Chicago Booth Review
Abstract
We study the economic consequences of managers' vocal delivery quality during earnings conference calls. We introduce a novel measure, vocal delivery quality, that captures the acoustic comprehensibility of audio information for an average listener. Our measure relies on a deep-learning algorithm applied to a large sample of earnings call audio files. Consistent with predictions from the psychology and accounting literatures, we find evidence that the quality of managers' vocal delivery deteriorates when they deliver negative news, such as a decrease in earnings or negative narrative information, and positive but transitory earnings news. We show that the stock market reacts in real time to managers' vocal delivery quality. We also document that the vocal delivery quality has an effect on information intermediaries such as analysts and the media. Overall, our findings underscore the role of vocal dimensions in corporate oral disclosures.
[3] Box Jumping: Portfolio Recompositions to Achieve Higher Morningstar Ratings
Co-authors: Lauren Cohen (HBS), and Eric So (MIT)
Based on my 3rd-year paper
Presented at: 2023 Rising Scholars Conference, MIT, University of Massachusetts Lowell, University of Miami, , Fuller Thaler Asset Management, Harvard Law School, York University, Southern Methodist University
Press coverage: Harvard Law School Forum on Corporate Governance
Abstract
We show a novel mechanism by which mutual fund managers strategically alter their portfolios to take advantage of investors' reliance on Morningstar star ratings. Specifically, funds achieve higher ratings by changing their holdings to induce Morningstar to reclassify them into size/value style boxes with lower average performance, thereby enabling more favorable peer comparison. This practice, which we term `box jumping', attracts fund flows and higher fees, despite sacrificing return performance and the ratings upgrades reversing within three years on average. These patterns emerge after 2002 when Morningstar ratings began to be based on relative performance within style boxes, and are predictably absent beforehand. We also show that pervasive box jumping creates negative spillover effects on other funds. Together, our findings highlight portfolio recomposition as a novel and strategic lever that funds use to manipulate Morningstar ratings, and that funds box jump despite compromising returns due to investors' fixation on ratings when allocating capital.
[4] AI, Decisions, and Information Inequality
Co-authors: Alex Kim (U of Chicago), Maxi Muhn (U of Chicago), Valeri Nikolaev (U of Chicago), and Eric So (MIT)
Abstract
[5] The Price to be Green: Evidence from Securities Lending by ESG Funds
Co-authors: Ki-Soon Choi (Boston College)
Presented at: Boston College, MIT, 2024 New England Accounting Research Symposium
Abstract
The literature and anecdotal evidence offer conflicting predictions regarding the relationship between ESG investing and securities lending. Despite the increasing incidence of securities lending by passive funds generally, we find that this is not the case for passive ESG funds. Using high-dimensional fixed effects, we show that passive ESG funds lend 30% less than non-ESG funds at both the fund and stock levels, even when they are holding the same stocks. The forgone revenue is equivalent to 20% of their expenses. We evaluate several explanations and find that our results are consistent with the idea of social norms in investing, where the negative connotation of short-selling labels lending as undesirable behavior for investors pursuing ESG. We add to the understanding of ESG investors' nonpecuniary motivations by quantifying the financial benefits that ESG investors forgo in the securities lending market.
Work In Progress
[6] Accounting Software Adoption Through the Lens of Directed Technological Change
Co-authors: Andrew Sutherland (MIT), and Felix Vetter (MIT)
Research Interests
My broader interests lie at the intersection of information, technology (e.g., cybersecurity, AI), and equity investing. The accompanying figure illustrates how my body of work relates to this overarching research theme.
I am also deeply engaged in exploring the recent advancements in generative AI and their implications for information processing in capital markets. I am exploring this emerging area of interest in several projects.