Forging the Future of Work
From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses
Journal of Financial Economics, July 2024
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. Documented synergies between humans and machines inform how humans can leverage their advantage for better adaptation to the growing AI prowess.
Sean Cao, Robert H. Smith School of Business, University of Maryland
Logistics Service Provider Technology Report
Logistics Service Provider Technology Report
The Logistics Service Provider Technology Report (LSPTR) will be an annual report published by the University of Maryland’s Supply Chain Management Center that aims to provide technology spend visibility for logistics service providers (LSPs) in a variety of areas.
We find that LSPs do not know how much to invest in technology because public filings do not disclose specifics about IT spend, consulting firms have limited data to back their perspectives, and industry analysts are bias and do not collect hard data. Shippers also cannot compare providers' technology capabilities or investments due to LSPs alignment with strategy being unclear despite marketing various capabilities, and they cannot compare their partners’ technology investment within their segment or the broader market.
Publishing an annual technology report compiling technology spend data will provide a solution to the identified problems and create value for stakeholder groups including, but not limited to: LSPs, software vendors, hardware vendors, shippers, industry associations, trade groups, shareholders, and consulting firms.
The report will encompass all technology-related expenditures of the companies who opt in to provide a complete perspective of LSP interest, activity, and spend on technology, with an initial proof-of-concept/pilot addressing 2 key sub-sets of technology in 2025: AI and robotics.
Geoff Milsom - UMD Professor
Jaclyn Wilton - Advisor
Maggie McGuire - Fellow
Ryan Sachar - UMD Undergraduate Student
Ivy Zheng - UMD Undergraduate Student
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. Further tests indicate that a key mechanism driving the improvement in forecast accuracy is that AI adoption helps mitigate the adverse effects of analyst decision fatigue and optimism bias. Finally, we find that forecast revisions made by AI-powered analysts are more informative to capital markets. Overall, our evidence points to the advantageous impact of AI on information production capabilities of financial analysts.
Michael Kimbrough, Musa Subasi, Yang Liu