Learning From Disagreement in the US Treasury Bond Market

• 成果类型: Article
• 署名作者: Giacoletti, Marco; Laursen, Kristoffer T.; Singleton, Kenneth J.
• 署名单位: University of Southern California; Stanford University; National Bureau of Economic Research
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.1111/jofi.12971
• 发表日期: 2021
• 页码: 395-441
• 关键词: term structure models; BLOCK BOOTSTRAP; RISK; determinants; expectations; uncertainty; premia

摘要

We study risk premiums in the U.S. Treasury bond market from the perspective of a Bayesian econometricianBLwho learns in real time from disagreement among investors about future bond yields. Notably, disagreement has substantial predictive power for yields, andBL's risk premiums are less volatile than those in the analogous model without learning.BL's forecasts are substantially more accurate than the consensus forecasts of market professionals, particularly following U.S. recessions. The predictive power of disagreement is distinct from the (much weaker) one of inflation and output growth. Rather, it appears to reflect uncertainty about future fiscal policy.