Taken in Sept. 2022 at LSE by Simin Chen.
Welcome to my site!
I am a lecturer in finance at Essex Business School, University of Essex. I obtained my PhD in economics from LSE. My current research is on expectations formation and its macro and finance implications, and I am broadly interested in empirical macroeconomics and finance.
Contact: junyi.liao@essex.ac.uk twitter
Over/Underreaction to New Information and Noise in Expectations Formation Link (revise&resubmit, Management Science)
In forecast surveys of aggregate variables, there's a positive consensus-level correlation between forecast errors and revisions, but a negative individual-level correlation. Previous studies interpret this as aggregate-level underreaction and individual-level overreaction. I propose that noise in forecasts explains this discrepancy. A stylized model demonstrates that a negative individual-level coefficient doesn't necessarily indicate overreaction. By estimating a structural parameter for over/underreaction, I find that inflation forecasting demonstrates significant underreaction, while the model matches both individual and aggregate-level correlation coefficients. I study the implications of underreaction and noise in expectations in a permanent income hypothesis model.
Presented at: FIRS 2024, University of Essex 2024, Asia Meeting of Econometric Society 2023, Shandong University 2023, HKUST 2023, Jinan University 2023, Money, Macro and Finance Society 2023, China Financial Research Conference 2023
Adaptive Expectations and Reactions to Information Link (revise&resubmit, Economica)
This paper develops a model combining adaptive expectations with noisy signals and derives three coefficients and one impulse response function (IRF): the Coibion–Gorodnichenko (CG) coefficient capturing consensus underreaction, the Bordalo–Gennaioli–Ma–Shleifer (BGMS) coefficient capturing individual overreaction, the Kohlhas–Walther (KW) coefficient capturing extrapolation, and the Angeletos–Huo–Sastry (AHS) IRF capturing delayed overshooting. There exists a parameter region in which the model reconciles all four moments with the data simultaneously. The model also delivers a testable prediction linking the CG coefficient to variable persistence, distinguishing adaptive expectations from Kalman-filter updating, and I present supporting evidence for adaptive expectations. The model’s fit to survey data is evaluated.
EC220 Introduction to Econometrics, London School of Economics 2018-2019
EC400 Mathematics for Macroeconomics and Microeconomics, London School of Economics 2018-2021
EC210 Macroeconomic Principle, London School of Economics 2019-2023
BE334 Financial Market and Monetary Policy, University of Essex 2023-2025
BE364 Global Trading on the Financial Market, University of Essex 2023-2024
BE357 Behavioral Finance, University of Essex 2024-2025