Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 30th Sept 2023, 08:42:51am CEST

Session Overview
2A: Analysts and information acquisition
Monday, 15/May/2023:
3:30pm - 5:00pm

Session Chair: Petri Jylhä
Location: Room Z014

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All in a Day's Work: What Do We Learn from Analysts' Bloomberg Usage?

Azi Ben-Rephael2, Bruce Carlin3, Zhi Da4, Ryan Israelsen1

1Michigan State University, United States of America; 2Rutgers University; 3Rice University; 4Notre Dame University

Discussant: Rawley Heimer (Arizona State University)

We use minute-by-minute Bloomberg online status data to characterize two important dimensions of sell-side equity analysts' work habits: we estimate the average workday length (AWL) to proxy for analysts' general effort provision and we use the percentage away day (PAD) to proxy for their soft information production. Both AWL and PAD vary much more across analysts than across time. Controlling for coverage, AWL is positively related to the quantity and the timeliness of analyst forecasts, while PAD is negatively related to quantity. Both are positively related to forecast accuracy, even after controlling for analyst fixed effects. COVID lockdown provides further causal evidence. Traveling analysts (with high pre-COVID PAD) experience a significant reduction in forecast accuracy during the lockdown. Using pre-COVID analyst commute time to instrument increased AWL during the lockdown, we find a higher AWL to significantly increase output and improve the accuracy of the forecasts.

What Do Questions Reveal? Skill Acquisition, Detection, and Recognition in the Capital Markets

Ling Cen1, Yanru Han1, Jarrad Harford2

1The Chinese University of Hong Kong; 2University of Washington

Discussant: Tamara Nefedova (ESCP Business School)

We construct an ex ante topic-specific skill measure based on the frequency of topic-specific questions that analysts raised in past earnings conference calls. In a supply chain information setting, we show that analysts with supply-chain-specific skill achieve a greater improvement in forecast accuracy relative to their peers when the firms experience firm-specific or market-wide supply-chain shocks. Analysts acquire skills through cross-brokerage learning and within-brokerage coaching. While brokerage firms do not assign tasks according to topic-specific skills, evidence based on the market reactions to recommendation updates and the information diffusion speed along the supply chain suggests that investors do recognize these skills. Overall, we provide a generalizable method that penetrates the black box of information processing and study the skill acquisition, detection, and diffusion in the capital market.

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