Chenjie Xu

Ph.D. Candidate in Finance, HKUST Business School, Hong Kong University of Science and Technology

Research Interests:

Macro-Finance, Empirical Asset Pricing

Contact Information:

Rm 4063, Lee Shau Kee Bldg, Hong Kong University of Science and Technology, Hong Kong
Tel: (+852) 97948792

You can find my resume here [Download].

Teaching Experience

FINA2203 - Fundamentals of Business Finance

Teaching Assistant
2017 Fall

FINA 7900B - Theoretical Asset Pricing

Guest Instructor on Special Topic
2017 Spring

FINA5360 - Fixed Income Analysis (MSc in Investment Management)

Teaching Assistant
2015 Fall

FINA5290 - Derivative Analysis (MSc in Investment Management)

Teaching Assistant
2014 Fall

FINA4403 - International Finance (UG course)

Teaching Assistant
2014 & 2015 Spring

Working Papers

Idiosyncratic Tail Risk and the Credit Spread Puzzle (Job Market Paper)

Presented at: RES PhD Meeting 2018 (scheduled), HKUST 2018, HKUST Finance Symposium Poster Session 2017.

This paper studies the asset pricing implications of idiosyncratic labor income tail risk on credit spread. I propose a model featuring incomplete market, heterogeneous households with recursive preference, and comovement of tail risk in labor income and firm cash flow growth. The model produces strong covariation of households' marginal utility and default rates, which helps to explain the stylized fact that the credit spread (1) is on average large and (2) is positively related to labor tail risk. Quantitatively, the tail risk premium can account for as much as 68% of the observed credit spread. My framework provides a new insight, drawn from an option perspective, that the implications of idiosyncratic tail risk for equity and bond can be very different.


Learning and the Capital Age Premium

Presented at: Econometric Society Winter Meeting 2018 (scheduled), 2019 MFA Conference (scheduled),AFA Poster Session 2019 (scheduled)*, HKUST 2018.

This paper studies the implications of parameter learning on the cross-section of stock returns. We propose a production-based general equilibrium model to study the link between capital age, timing of cash flows and expected returns in the cross-section of stocks. Our model features slow learning about firms' exposure to aggregate productivity shocks over time. Firms with old capital are assumed to have more information about their exposure than firms with young capital. Our framework provides a unified explanation of the following stylized empirical facts: old capital firms (1) have higher capital allocation efficiency; (2) are more exposed to aggregate productivity shocks and hence earn higher expected returns, which we call it the capital age premium; (3) have shorter cash-flow duration, as compared with young capital firms.



Hong Kong University of Science and Technology

ph.d., finance, expected: summer 2019
2013 - 2019

Peking University

M.S., finance, Jul 2013
B.S., economics, Jul 2011
B.S., mathematics, Jul 2011
2007 - 2013