Chao Jiang
Associate Professor of Finance (2022-present)
Assistant Professor of Finance (2016-2022)
Darla Moore School of Business, University of South Carolina
1014 Greene Street, Columbia, SC 29208
Email: chao.jiang AT moore.sc.edu
EDUCATION
Ph.D. in Finance, University of Kansas 2016
M.A. in Economics, Central Michigan University
B.A., Shandong University of Finance and Economics, China
RESEARCH INTERESTS
Empirical Asset Pricing, Behavioral Finance, Insider Trading, Empirical Corporate Finance
PUBLICATIONS
Indirect Insider Trading, Journal of Financial and Quantitative Analysis, forthcoming (with Brad Goldie, Paul Koch, and Jide Wintoki).
“Overnight Returns, Daytime Reversals, and Future Stock Returns,” Journal of Financial Economics, Volume 145, Issue 3, September 2022, Pages 850-875 (with Ferhat Akbas, Ekkehart Boehmer, and Paul Koch).
“Insider Trading and the Legal Expertise of Corporate Executives,” Journal of Banking and Finance, Volume 127, June 2021, 106114 (with Jide Wintoki and Yaoyi Xi).
“Insider Investment Horizon,” Journal of Finance, 2020, 75: 1579-1627 (with Ferhat Akbas and Paul Koch).
“Offshore Expertise for Onshore Companies: Director Connections to Island Tax Havens and Corporate Tax Policy,” Management Science, 2018, Volume 64, Issue 7, July, pp. 2973-3468 (with Tom Kubick, Mihail Miletkov, and Jide Wintoki).
“The Trend in Firm Profitability and the Cross Section of Stock Returns,” The Accounting Review, September 2017, Vol. 92, No. 5, pp. 1-32 (with Ferhat Akbas and Paul Koch).
“Designing a Proper Hedge: Theory versus Practice,” Journal of Financial Research, 2016, Volume 39, Issue 2 Summer, pp. 123-144 (with Ira Kawaller and Paul Koch).
WORKING PAPERS
[1] The Cash Cycle Surprise and Future Stock Returns
The cash cycle measures the time it takes for a company to complete its entire business process from inventory payment to cash collection. We introduce a measure of the cash cycle surprise (CCS) and show that it negatively predicts future stock returns. This predictive relationship is robust to controlling for the cash cycle and other determinants of stock returns. The CCS also forecasts earnings surprises and analyst forecast errors. Furthermore, the results are more pronounced for stocks with greater limits to arbitrage and following periods of elevated market sentiment. The results are best explained by investor underreaction.
[2] High Aggregate Volume Return Premium, with Ferhat Akbas, Egemen Genc, and Paul Koch
Unusually high aggregate stock trading volume in one week predicts higher excess market returns in the following week, especially when accompanied by high market volatility. This predictive relation is robust across alternative measures of aggregate trading volume. In out-of-sample forecasting tests, unusually high aggregate volume outperforms a host of other variables that have been shown to forecast the equity premium. Our evidence is most consistent with a risk premium associated with shocks to market-wide disagreement among market participants. Return autocorrelations, visibility effects, and market sentiment do not explain our findings.
[3] Margin Requirements, Risk Taking, and Multifactor Models, with Ferhat Akbas, Lezgin Ay, and Paul Koch
When investors anticipate the Fed increasing margin requirements, they bid up the riskier stocks in the long legs of hedge portfolios associated with the market, HML, and SMB factors relative to the less risky stocks in the short legs. Following such a policy change, the returns on these hedge portfolios decline, implying lower subsequent compensation for bearing the risk associated with these three factors. In contrast, margin requirements are unrelated to returns on the momentum factor. Our evidence suggests that investors adjust their risk exposures to the market, SMB, and HML factors when leverage constraints are changed, but not momentum.
[4] Debtor Protection, Credit, and Local Crime, with John Hackney