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.
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.
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.
Risk Matters: Cyber Risk and AI – The Changing Landscape
Cyber risk is a top concern for organizations worldwide, intensified by AI's dual role in bolstering defenses and enhancing attacks. The Gordon-Loeb Model offers a cost-benefit framework to optimize cybersecurity investments, emphasizing AI's evolving, game-theoretic complexities.
TerpTax Alert: Unexpected $1,400 IRS Payments, Some in Error, to F-1 Students
Some F-1 visa students at UMD are receiving $1,400 IRS payments due to errors in stimulus eligibility. TerpTax, led by accounting lecturer Samuel Handwerger, advises returning these payments to avoid future tax and immigration complications. Assistance is available through TerpTax.
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.
Vigilance, Resilience, Flexibility as Keys to Countering Evolving Cyber Threats
Experts from the Smith School of Business and School of Public Policy convened for the 20th Financial Information Systems and Cybersecurity Forum, addressing cyber risk management through vigilance, resilience, and flexibility amid evolving threats and emerging technologies.
Scammers Meet Their Match: Student Fraud Investigators Spot Rising Threat
When University of Maryland students in the Justice for Fraud Victims project received suspicious job offers via text, their fraud investigation skills—sharpened under faculty advisor Samuel Handwerger at the Smith School—helped uncover "task scams," a scheme costing victims $220M since 2020.