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SUMMARY:All in a day's work: What do we learn from Analysts' Bloomberg Usa
 ge?
DTSTART:20221104T103000
DTEND:20221104T120000
DTSTAMP:20260510T091527Z
UID:0651306ec3193f591e5306b41d41cb654419ba59cc857cae796f47a8
CATEGORIES:Conferences - Seminars
DESCRIPTION:Zhi Da\, Notre Dame\nWe use minute-by-minute Bloomberg online 
 status data to characterize two important dimensions of sell-side equity a
 nalysts' work habits: we estimate the average workday length (AWL) to prox
 y for analysts' general effort provision and we use the percentage away da
 y (PAD) to proxy for their soft information production. Both AWL and PAD v
 ary much more across analysts than across time. Controlling for coverage\,
  AWL is positively related to the quantity and the timeliness of analyst f
 orecasts\, while PAD is negatively related to quantity. Both are positivel
 y related to forecast accuracy\, even after controlling for analyst _fixed
  effects. COVID lockdown provides further causal evidence. Traveling analy
 sts (with high pre-COVID PAD) experience a significant reduction in foreca
 st accuracy during the lockdown. Using pre-COVID analyst commute time to i
 nstrument increased AWL during the lockdown\, we _find a higher AWL to\nsi
 gnificantly increase output and improve the accuracy of the forecasts.\n 
LOCATION:UniL Campus\, Room Extra 126
STATUS:CONFIRMED
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