Jun Li

I am an Associate Professor in finance at University of Texas at Dallas. My research lies in the area of empirical and theoretical asset pricing, and focuses on the time series and cross-sectional variations of asset returns.

I am on sabbatical leave in fall 2019 and currently visiting Wharton.

Office 14-510
Jindal School of Management
University of Texas at Dallas
800 West Campbell Road
Richardson, TX 75080
United States

Phone: (972) 883-4422
Email: jun.li3@utdallas.edu

Curriculum Vitae

Jun Li

 

WORKING PAPERS

1. "Expected investment growth premium" (with Huijun Wang) [SSRN]

Abstract: A neoclassical model with investment lags predicts that a firm's risk premium increases with its planned investment. Using a novel measure of investment plans, namely, expected investment growth (EIG), we document that high EIG firms earn an annualized return that is 15.4% higher than low EIG firms in the US sample from July 1968 to December 2016. This EIG premium cannot be captured by leading asset pricing models and is confirmed in various robustness checks. Further analyses provide empirical evidence for the embedded leverage effect of planned investment, which creates cross-sectional heterogeneity in the exposure to business cycle risk.

- 2018 Crowell Third Prize
-Presented at Hong Kong University of Science and Technology, Chinese University of Hong Kong, City University of Hong Kong, Hong Kong Polytechnic University, Nanyang Technological University, University of Delaware, Baylor University, 2017 BI CAPR's Workshop on Investment and Production Based Asset Pricing, China International Conference in Finance, Baltimore Area Finance Conference, the 5th SAFE Asset Pricing Workshop, the 2nd Wellington Finance Summit, PanAgora Asset Management, and Financial Management Association Annual Meeting.

2. "The opposing effects of information complexity and information content on return volatility" (with Frederico Belo, Xiaoji Lin, and Xiaofei Zhao) [SSRN]

Abstract: We evaluate the impact of complexity and content of new information on stock return volatility dynamics around 10-K fillings. On average, return volatility increases by 0.4% in the first four weeks after the release of the report, followed by a 2.6% decrease in the subsequent six weeks. This hump-shaped dynamics is more pronounced for firms with larger 10-K reports. The effects are economically significant: an options-based investment strategy exploring the volatility dynamics generates 17.3% annualized return spread. Our findings highlight the importance of timing for understanding the opposing effects of complexity and content of new information on asset prices.

- Revise and Resubmit, Management Science
- 2015 Crowell Second Prize
- Semifinalist for the 2016 FMA Best Paper Award in Investment
- Presented at University of Waterloo, University of Oklahoma, PanAgora Asset Management, Cubist, American Finance Association Annual Meeting, Lone Star Finance Conference, Mid Atlantic Finance Research Conference in Finance, Midwest Finance Association, China International Conference in Finance, Financial Management Association Annual Meeting

3. "Aggregate expected investment growth and stock market returns" (with Huijun Wang and Jianfeng Yu) [SSRN]

Abstract: Consistent with neoclassical models with investment lags, we find that a bottom-up measure of aggregate investment plans, namely, aggregate expected investment growth (AEIG), negatively predicts future stock market returns, with an adjusted in-sample R-squared of 18.5% and an out-of-sample R-squared of 16.3% at the one-year horizon. The return predictive power is robust after controlling for popular macroeconomic return predictors, in subsample periods, as well as in other G7 countries. Further analyses suggest that the predictive ability of AEIG is more likely to be driven by the time-varying risk premium than by behavioral biases such as extrapolative expectations.

-Presented at Asian Development Bank Institute, Peking University, University of International Business and Economics, University of Sydney, SFS Cavalcade, BI CAPR's Workshop on Investment and Production Based Asset Pricing, China International Conference in Finance, Northern Finance Association Annual Meeting, Asian Finance Association Annual Meeting, 29th Annual Conference on Financial Economics and Accounting, and SGF Conference.

4. "Is the size premium really driven by firm size?" (with Zhiyao Chen and Huijun Wang) [SSRN]

Abstract: Not really. Decomposing firm size into horizon-based components, we find that size five years ago explains 80% of the current size but has little predictive power for future returns. In contrast, the change in size over the prior two to five years explains only 18% of the size but completely captures the size premium. Our decomposition relates the size premium to other known asset pricing phenomena, and we replicate these findings in a simple no-arbitrage valuation model with two factors. Our analysis provides new insights into the disappearance of the size premium and the behavior of new entrants.

-Earlier versions ciruclated under the title "Decomposing the size premium"
-Presented at Midwest Finance Association Annual Meeting, China International Conference in Finance, Financial Management Association Annual Meeting, and SGF Conference.

WORKS IN PROGRESS

1. "Operating hedge and gross profitability premium" (with Leonid Kogan and Harold H. Zhang)

Abstract: In this paper we explore the hedging effect induced by variable costs in production, and its impact on fundamental risk of firm cash flows and stock returns. The hedging effect varies across firms and is weaker for more profitable firms. This leads to more profitable firms having a higher exposure to aggregate profitability shocks, giving rise to a gross profitability premium. Our model captures coexistence of the negatively correlated gross profitability and value factors, addressing an empirical pattern that poses a challenge to the models relying on operating leverage as the primary source of the value premium.

-Presented at MIT Sloan, University of Oklahoma, Cambridge University, Northeastern University, Tsinghua PBC School of Finance, Peking University, Renmin University of China, SFS Cavalcade, Western Finance Association Annual Meeting, the 2nd Corporate Policies and Asset Prices, Midwest Finance Association, the Swedish House of Finance conference on Financial Markets and Corporate Decisions, 2019 Jacobs Levy Center Conference, 2019 Annual Conference on Financial Economics and Accounting, and China International Conference in Finance. To be presented at 2020 AFA meeting.

2. "Operating leverage and hedging: A tale of two production costs for asset pricing" (with Leonid Kogan, Harold H. Zhang, and Yifan Zhu)

3. "Asset composition, stochastic volatility and cross-sectional stock returns" (with Zhiyao Chen and Kai Li)

PUBLICATIONS

1. "Investor attention, psychological anchors, and stock return predictability" (with Jianfeng Yu), Journal of Financial Economics, Vol. 104, pp. 401-419, May 2012 [SSRN]

2. "Government spending, political cycles and the cross section of stock returns" (with Frederico Belo and Vito Gala), Journal of Financial Economics, Vol. 107(2), pp. 305-324, Feb 2013 [SSRN]

3. "Asset pricing in production economies with extrapolative expectations" (with David Hirshleifer and Jianfeng Yu), Journal of Monetary Economics, Vol. 76, pp. 87-106, Nov 2015 [SSRN] Internet Appendix

4. "Short-run and long-run consumption risks, dividend processes, and asset returns"(with Harold H. Zhang), Review of Financial Studies, Vol. 30, pp. 588-630, Feb 2017 [SSRN] Internet Appendix

5. "Explaining momentum and value simultaneously", Management Science, Vol.64(9), pp.4239-4260, Sep 2018 [SSRN]

6. "Labor-force heterogeneity and asset prices: the importance of skilled labor" (with Frederico Belo, Xiaoji Lin, and Xiaofei Zhao), Review of Financial Studies, Vol. 30, pp. 3669-3709, Oct 2017 [SSRN]. Industry level labor skill data here.

PERMANENT WORKING PAPERS

1. "Expected Investment Growth and Cross Sectional Stock Returns" (with Huijun Wang), [SSRN]


TEACHING

FIN 6392, Financial Technology and Data Analytics: Spring 2019

FIN 3320, Business Finance: Spring and Fall 2018

FIN 4300, Investment Management: Spring 2013-2017

FIN 7335, Topics in Empirical Asset Pricing: Spring 2015, 2017, Fall 2018