Under- and Over-Reaction in Yield Curve Expectations


I study how professional forecasts of interest rates across maturities respond to new information. I document that forecasts for short-term rates underreact to new information while forecasts for long-term rates overreact. I propose a new explanation based on ``autocorrelation averaging,’’ whereby, due to limited cognitive processing capacity, forecasters’ estimate of the autocorrelation of a given process is biased toward the average autocorrelation of all the processes they observe. Consistent with this view, I show that forecasters over-estimate the autocorrelation of the less persistent term premium component of interest rates and under-estimate the autocorrelation of the more persistent short rate component. A calibrated model quantitatively matches the documented pattern of misreaction. Finally, I explore the pattern’s implication for asset prices. I show that an overreaction-motivated predictor, the realized forecast error for the 10-year Treasury yield, robustly predicts excess bond returns.


Hong Kong University of Science and Technology, Cheung Kong Graduate School of Business, University of Hong Kong, National University of Singapore, Chinese University of Hong Kong, Notre Dame, Michigan Ross, University of Florida, Cornerstone Research, Yale SOM, 2021 WFA