BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Learning From Disagreement in the U.S. Treasury Bond Market
DTSTART:20190614T103000
DTEND:20190614T120000
DTSTAMP:20260510T165015Z
UID:255f167ed3970bea99d7bfd7277cdcc88fe0a5cbaf3816a22131ff2d
CATEGORIES:Conferences - Seminars
DESCRIPTION:Kenneth J. SINGLETON\, Stanford University\nWe study the evolu
 tion of risk premiums on US Treasury bonds from the perspective of a real-
 time Bayesian learner BL who conditions her beliefs on measures of disagre
 ement among professional forecasters about the future paths of bond yields
 . Learning about historical yields and disagreement within a dynamic term 
 structure model leads to substantial variation in BL's subjective expected
  excess returns on bonds. The informativeness of disagreement is shows to 
 be distinct from the (much weaker) forecasting power of inflation and outp
 ut growth. Rather\, it appears to be reflect policy uncertainty and\, in p
 articular\, uncertainty about fiscal policy. BL's learning rule substantia
 lly outperforms consensus forecasts of market professionals\, particularly
  following U.S. recessions.
LOCATION:UNIL\, Extranef\, room 126 https://planete.unil.ch/plan/?local=EX
 T-126
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR