Building credible commitments via board ties: Evidence from the supply chain
Using a novel dataset that provides a comprehensive coverage of U.S. firms' industrial supply chain relationships, we find that firms with innovation specific to a buyer are more likely to share a common director with that buyer. This association is stronger when the buyer has a larger number of alternative suppliers. We further find that when a supplier–buyer pair shares a common director, the supplier's R&D investment is more sensitive to the investment opportunities of its buyer. Moreover, such pairs tend to have longer supply chain relationships.
Biodiversity Entrepreneurship
We study an emerging class of start-up organizations focused on biodiversity conservation and the challenges they face in financing these ventures. Using a novel machine learning method, we identify 630 biodiversity-linked start-ups in PitchBook and compare their financing dynamics to other ventures. Biodiversity start-ups raise less capital but attract a broader coalition of investors, including not only venture capitalists (“value investors”) but also mission-aligned impact funds and public institutions (“values investors”).
Analytics for Finance and Accounting: Data Structures and Applied AI
Analytics for Finance and Accounting: Data Structures and Applied AI bridges the gap between technical data science education and domain-specific applications in accounting and finance. Designed for students and instructors seeking practical exposure to AI-driven financial analytics, the book prioritizes understanding real-world business data—structured and unstructured—before introducing machine learning techniques.
From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses
An AI analyst trained to digest corporate disclosures, industry trends, and macroeconomic indicators surpasses most analysts in stock return predictions. Nevertheless, humans win “Man vs. Machine” when institutional knowledge is crucial, e.g., involving intangible assets and financial distress. AI wins when information is transparent but voluminous. Humans provide significant incremental value in “Man + Machine”, which also substantially reduces extreme errors. Analysts catch up with machines after “alternative data” become available if their employers build AI capabilities.
EPA Scrutiny and Voluntary Environmental Disclosures
Market participants have called on the SEC to address the lack of disclosures about firms’ environmental impacts, investments, and exposures. However, the frictions that obstruct the flow of environmental information are not well understood. I shed light on these frictions by examining whether scrutiny by the Environmental Protection Agency (EPA) restricts the firm’s voluntary environmental disclosures in earnings conference calls.
CFO Narcissism and the Power of Persuasion Over Analysts: A Mixed-Methods Approach
We study the role of CFO narcissism in the intent and ability to positively influence sell-side analysts’ perceptions of the firm. Consistent with narcissists casting favorable impressions on others, we find CFO narcissism is associated with overly optimistic analyst valuations. We then study public persuasion attempts by analyzing conference call transcripts and private persuasion attempts through a laboratory study.
AI-powered Analysts
We explore how brokerage firms’ investments in artificial intelligence (AI) affect their analysts’ information production. We find that analysts employed at brokerage firms with greater AI integration issue more accurate earnings forecasts. Cross-sectional analyses reveal that AI’s benefits are more pronounced for analysts with less firm-specific experience and when the firm’s disclosures are more readable.
Do Credit Rating Agencies Learn from the Options Market?
Do credit rating agencies (CRAs) learn from the options market? We examine this question by exploring the relation between options trading activity and credit rating accuracy. We find that as options trading volume increases, credit ratings become more responsive to expected credit risk and exhibit greater ability to predict future defaults. We also find that CRAs rely more on the options market as a source of ratings-related information when firm default risk is higher, options trading is more informative, manager-provided information is of lower quality, and firm uncertainty is higher.
How to Talk When a Machine Is Listening: Corporate Disclosure in the Age of AI
Growing AI readership (proxied for by machine downloads and ownership by AI-equipped investors) motivates firms to prepare filings friendlier to machine processing and to mitigate linguistic tones that are unfavorably perceived by algorithms. Loughran and McDonald (2011) and BERT available since 2018 serve as event studies supporting attribution of the decrease in the measured negative sentiment to increased machine readership. This relationship is stronger among firms with higher benefits to (e.g., external financing needs) or lower cost (e.g., litigation risk) of sentiment management.
Seductive Language for Narcissists in Job Postings
Prior research indicates that narcissistic executives engage in earnings management and other negative organizational behaviors, and many studies ponder why firms hire such individuals, especially into corporate accounting positions.