Topic: Time-Varying Ambiguity and Asset Pricing Puzzles

Speaker: Zhan Shi, Visiting Assistant Professor of Finance, The Ohio State University

Date: July 14^th (Tue.)

Time: 10:00-11:30am  

Location: Building 4, Room 101

Language: English

Abstract:

This paper studies the effects of time-varying Knightian uncertainty (ambiguity) on asset pricing in a Lucas exchange economy. Specifically, I consider a general equilibrium model where an ambiguity-averse agent applies a discount rate that is adjusted not only for the current magnitude of ambiguity but also for the risk associated with its future fluctuations. As such, both the ambiguity level and volatility help raise asset premia and accommodate richer dynamics of asset prices. With a novel measure for the ambiguity level, I show that the estimated model is able to match the key moments of equity premium and risk-free rate. More importantly, it explains the credit spread puzzle despite a low default probability. The model also accounts for a wide range of dynamic asset pricing phenomena, including the procyclical variation of stock prices, the countercyclical variation of credit spreads, the long-horizon predictability of stock returns and credit spreads, and the low correlation between asset prices and consumption growth. Furthermore, the proposed ambiguity measure is found to exhibit significant predictive power for excess returns on equities and bonds as well as for corporate yield spreads, a finding that justifies uncertainty channels highlighted in the model.

About the speaker:

Zhan Shi is Visiting Assistant Professor of Finance at The Ohio State University. Dr. Shi pursued his PhD course work at the Pennsylvania State University Smeal College of Business after earning a BS in statistics from Fudan University. His research interests include fixed income, macro-finance, asset pricing and financial econometrics. Shi’s research has been presented at the American Finance Association Meeting, Northern Finance Association Meeting, the Singapore International Conference on Finance and numerous additional professional conferences. He is the co-author of the chapter “Model Selection for High-Dimensional Problems” in the Handbook of Financial Econometrics and Statistics. Shi's research won the Cubist Systematic Strategies PhD Candidate Award from the WFA, 2014. His teaching experience includes courses on Derivative Markets as well as Security Analysis and Portfolio Management.