Seminar: Real-Time Bayesian Learning and Bond Return Predictability
Room 7-208, 7/F, Lau Ming Wai Academic Building

The paper examines statistical and economic evidence of out-of-sample bond return predictability for a real-time Bayesian investor who learns about parameters, hidden states, and predictive models over time. We find some statistical evidence using information contained in forward rates. However, such statistical predictability cannot generate any economic value for investors. Furthermore, strong statistical and economic evidence from fully revised macroeconomic data vanishes when real-time and survey-based macroeconomic information is used. We also show that highly levered investments in bonds can improve short-run bond return predictability.

Event Speaker
Prof. Junye Li

Junye Li is a Professor of Finance at ESSEC Business School. He holds a Master of Engineering in Systems Engineering from Beijing Jiaotong Univeristy (China), and a PhD in Economics from Bocconi University (Italy). His research interests include Empirical Asset Pricing, Volatility Modeling, Derivatives, and Financial Econometrics. His recent research has appeared in Review of Financial Studies, Journal of Econometrics, Journal of Financial and Quantitative Analysis, Journal of Money, Credit and Banking, Journal of Business and Economic Statistics, and so on.