Jinfei Sheng
Assistant Professor of Finance
Merage School of Business
University of California, Irvine
Research Interests:
Empirical Asset Pricing, Investments, Behavioral Finance, AI & FinTech, Textual Analysis
Embedded Files
Publications
Publications
Macroeconomic Attention and Announcement Risk Premia, Review of Financial Studies, 35 (2022), 5057–5093.
(with Adlai Fisher and Charles Martineau) RFS Internet Appendix MAI Data
Abstract: We construct macroeconomic attention indices (MAI), new measures of attention to different macroeconomic risks including monetary policy and employment. Individual MAI increase several days before a related announcement, on average. MAI also respond to changes in macroeconomic fundamentals, with bad news raising attention more than good news. Across announcements, attention predicts announcement risk premia and implied volatility changes with large economic magnitudes. Our findings support theories of endogenous attention and announcement risk premia while demonstrating future research directions, including that announcements can raise new concerns. Macroeconomic announcements are important not only for contents and timing, but also attention.
Macro News and Micro News: Complements or Substitutes?, Journal of Financial Economics, 145 (2022), 1006-1024.
Abstract: We study how the arrival of macro-news affects the stock market’s ability to incorporate the information in firm-level earnings announcements. Existing theories suggest that macro and firm-level earnings news are attention substitutes; macro-news announcements crowd out firm-level attention, causing less efficient processing of firm-level earnings announcements. We find the opposite: the sensitivity of announcement returns to earnings news is 17% stronger, and post-earnings announcement drift 71% weaker, on macro-news days. This suggests a complementary relationship between macro and micro news that is consistent with either investor attention or information transmission channels.
Cheaper Is Not Better: On the 'Superior' Performance of High-Fee Mutual Funds, Review of Asset Pricing Studies, 13 (2023), 375–404.
(with Mikhail Simutin and Terry Zhang) RAPS Internet Appendix
Abstract: In contrast with theoretical predictions, high-fee active equity funds generate worse net-of-expenses performance. We show that this fee-performance puzzle is driven by the preference of high-fee funds for stocks with low operating profitability and high investment rates, characteristics associated with low expected returns. After controlling for exposures to profitability and investment factors, high-fee funds significantly outperform low-fee funds before expenses and achieve similarly poor net-of-fees performance. In resolving the fee-performance puzzle, our findings provide support to the theoretical prediction that skilled managers extract rents by charging high fees, and challenge the common advice to prefer low-fee funds over high-fee counterparts.
Do Investors Affect Financial Analysts’ Behavior? Evidence from Short Sellers, Financial Management, 52 (2023), 199-224.
(with Yun Ke, Kin Lo, and Jenny Zhang) FM
Abstract: We examine how short sellers affect financial analysts’ forecast behavior using a natural experiment that relaxes short-sale constraints. We find that increased ease of short selling improves analyst earnings forecast quality by reducing forecast bias and increasing forecast accuracy. The improvements can be explained by both the disciplining pressure from short sellers and increased price efficiency from incorporating information in a timely manner. Although it is well documented that financial analysts can affect investors, our paper provides novel evidence on how sophisticated investors, short sellers, can affect analysts.
Partisan Return Gap: The Polarized Stock Market in the Time of a Pandemic, Management Science, 70 (2024), 5091–5114.
(with Zheng Sun and Wanyi Wang) MS Internet Appendix
Abstract: Using two proxies for investors’ political affiliation, we document sharp differences in stock returns between firms likely dominated by Democratic investors (blue stocks) and those dominated by Republican investors (red stocks) during the COVID pandemic. Red stocks have 20 basis points higher risk-adjusted returns than blue stocks on COVID news days (Partisan Return Gap). Lockdown policies, COVID cases, industry and firm fundamentals only explain at most 40% of the return gap. Polarized political beliefs about COVID, revealed through people’s social distancing behaviors, contribute to about 40% of the return gap beyond the fundamental channel. Our paper provides partisanship as a novel aspect in understanding abnormal stock returns during the pandemic.
Asset Pricing in the Information Age: Employee Expectations and Stock Returns, Review of Asset Pricing Studies, 15 (2025), 74-101.
Abstract: Firms with more positive employee expectations tend to earn higher future returns, delivering annualized abnormal returns ranging from 8% to 11%. Employees’ forward-looking expectations is a stronger return predictor than their satisfaction, which is backward-looking. Employee expectations can predict returns because they reflect firms’ fundamental information that has not yet reflected in traditional data sources, such as earnings reports. Hedge funds actively trade on this information, consistent with a decay in forecasting power over longer holding horizons. Overall, this paper highlights the importance of labor in asset pricing, specifically from the perspective of employee expectations.
Working Papers
Working Papers
Do Mutual Funds Walk the Talk? Evidence from Fund Risk Disclosure, 2024 (Revise & Resubmit, Review of Financial Studies)
XiYue Best Paper Award, CICF
Conference: Melbourne Asset Pricing Meeting, UNSW Asset Pricing Workshop, INFORMS Conference, UBC Summer Finance Conference, CICF, MFA, China Fintech Research Conference, China International Risk Forum, Future Finance Information Webinar, Workshop “Leveraging the latest advances in Natural Language Processing,” New Zealand Finance Meeting
Abstract: We examine the informativeness of fund risk disclosure by combining fund returns and textual data. Our novel measure, INF, quantifies the explanatory power of disclosed risks for fund returns. The average INF is 55%, after controlling for market risk, and remains at 26-29% after excluding risks related to fund name or strategy. We explain variations in INF through disclosure costs and benefits: 1) Funds with poor disclosure face SEC comment letters and reduced flow, 2) Informative disclosures attract institutional flows, and 3) Performance concerns may disincentivize proper disclosure. Overall, funds face important trade-offs between transparency and maintaining their competitive edge.
Generative AI and Asset Management, 2024 (Revise & Resubmit, Review of Financial Studies)
(with Zheng Sun, Baozhong Yang, Alan Zhang)
Conference: EFA, AI in Finance Conference, Asian Bureau of Finance and Economic Research Conference, CICF, Future of Financial Information Conference, SAIF Research Conference, SFS Cavalcade Asia-Pacific, University of Connecticut Finance Conference, The 1st Workshop on LLMs and Generative AI for Finance, ABFER-JFDS Conference on AI and Capital Markets | Media coverages: AI Street
Abstract: This paper proposes a novel measure of investment companies’ reliance on generative AI, focusing on its implications for hedge funds. We document a sharp increase in generative AI usage by hedge funds after ChatGPT’s 2022 launch. A difference-in-differences test shows that hedge funds adopting generative AI earn 3-5% higher annualized abnormal returns than non-adopters. We further identify this effect by exploiting ChatGPT outages as exogenous shocks. The outperformance originates from funds’ AI talent and ChatGPT’s strength in analyzing firm-specific information. Non-hedge funds yield no significant returns from AI adoption, suggesting generative AI may widen existing disparities among investors.
Demographics and Interest Rates: New Theory and Evidence, 2024 (Reject & Resubmit, Journal of Finance)
(with Jack Favilukis and Terry Zhang)
Conference: AFA, NFA, MFA, California Corporate Finance Conference
Abstract: Conventional wisdom is that aging populations lead to lower interest rates (Hansen (1939), Samuelson (1958)). We show the opposite is true for deposit rates if aging is driven by longer lifespans and if banks are oligopolists, because a longer retirement makes utility especially sensitive to interest rates, incentivizing shopping around, and raising the demand elasticity. Consistent with our model, empirically, deposit rates are significantly higher in older U.S. MSAs, especially ones with more bank competition. Deposit composition can explain half of the positive relationship as less liquid accounts like CDs offer higher rates and their owners are older.
Geopolitical Risk and Stock Returns, 2025 New
(with Zheng Sun, Qiguang Wang) Geopolitical Risk Index (GRI) and Trade War Index (TWI) T
Conference: UCSD KCFR IAC Meeting
Abstract: This paper systematically examines the relationship between geopolitical risk and stock market returns by constructing a comprehensive Geopolitical Risk Index (GRI) using textual analysis of Wall Street Journal archives from 1984 to 2025. Importantly, our GRI measure covers trade tensions and trade wars, which have been missing from the geopolitical index from the literature. We find that GRI positively predicts future aggregate market returns, with an out-of-sample R2 of 2.48%. A one-standard-deviation increase in GRI predicts an 8.71% increase in annualized excess returns in the following month in the U.S. market and between 2.97%–6.33% in global markets. The effects of geopolitical risk have intensified in recent years, rising to 13.21% for the U.S. and 8.25%–11.06% globally. The trade war component of the GRI has independent return forecasting power beyond the traditional geopolitical risk index. In the cross-section, stocks with greater exposure to geopolitical risk earn higher abnormal returns. The portfolio that longs stocks with high geopolitical risk and shorts those with low geopolitical risk delivers a 7.91% alpha in the subsequent month. Overall, our findings underscore the importance of geopolitical risk in asset pricing, highlighting its role in shaping investor expectations, market dynamics, and global equity premiums.
Trading in Twilight: Sleep, Mental Alertness, and Stock Market Trading, 2025 New
(with Hee-Seo Han, David Hirshleifer, and Zheng Sun) NBER NB
Conference: CFEA, CICF, MFA, International Behavioural Finance Conference, California Corporate Finance Conference | Media coverages: MarketWatch, Morningstar
Abstract: We test whether mental alertness, as proxied by sleep disruption, impairs investor trading performance. Using four complementary approaches, we document that retail investors who experience a later sunset time on average earn lower abnormal returns on their trades. These approaches include RDD based on time zone borders, comparison of different seasons and latitudes, panel regression with household fixed effects, and daylight saving changes. Further tests suggest that the sleep disruption effect derives from impaired investor attention.
Abstract: This paper studies the relationship between disagreement of the employee crowd and stock returns, utilizing online forecasts regarding their employers’ business outlook. Stocks with high disagreement tend to earn lower future returns. A trading strategy based on employee disagreement delivers an annualized abnormal return of -8% to -9%. This return predictability is attributed to the fundamental channel, as firms characterized by high employee disagreement tend to demonstrate lower profitability and less employee synergy. This information is incorporated into stock price gradually over time as this predictive power is sustained for two months. Overall, disagreement among online crowds is important for understanding stock returns.
Are Fund Disclosure Views Informative to the Stock Market?, 2024
(with Yichun He, Qiguang Wang)
Conference: CICF, Hawaii Accounting Research Conference
Abstract: We study how mutual fund disclosure views influence stock market informational efficiency. Using EDGAR log data, we document substantial investor interest in fund disclosures and their ability to identify informed holdings. We introduce a novel measure of information flow from fund disclosure views to the stock market, finding that it improves market efficiency, as reflected in price and trading reactions to earnings news. The effect is driven by sophisticated viewers engaged in multi-source information acquisition and trading. Although mutual funds tend to underperform on average, aggregated views of fund disclosures enhance market efficiency by providing valuable information to the market.
How Do Investors Value Technology in Cryptocurrency? Evidence from Textual Analysis, 2025
(with Yukun Liu and Wanyi Wang)
AMTD FinTech Centre Prize, Asian Finance Association Conference
Conference: CFEA, CICF, AFA Poster, EFA Poster, CARF Research Workshop on FinTech, Future of Financial Information Conference, Shanghai-Edinburgh Fintech Conference, Miami Research Conference on Machine Learning and Business, Hong Kong Conference for Fintech, AI, and Big Data in Business, UWA Blockchain and Cryptocurrency Conference, Global AI Finance Research Conference | Media coverages: Forbes, Duke FinReg Blog
Abstract: This paper examines how investors evaluate new technologies from the perspective of cryptocurrencies. Employing a machine learning method, we construct a novel Tech Index from whitepapers to capture technology sophistication of cryptocurrency. While cryptocurrencies with higher Tech Indexes are more likely to enjoy early success and a high first-day listing price, they tend to earn significantly lower subsequent returns after being listed. The return reversal is stronger when market sentiment is higher. Moreover, cryptocurrencies with higher Tech Index earn lower returns after the unexpected Luna Crash and FTX scandal. Overall, these findings suggest investors overreact to cryptocurrency technology.
Capitalizing on Retail Investor Sentiment: Evidence from FinTech ETFs, 2023
(with Bong Ko and Zheng Sun)
Conference: Bretton Woods Accounting and Finance Conference, Shanghai-Edinburgh-UCL Fintech Conference
Abstract: This paper studies how professional money managers respond to retail investors' sentiment toward new technology through the lens of FinTech ETFs. Retail investor sentiment about FinTech, measured by Google Search Volume, has tripled from 2015 to 2022. Using a hand-collected dataset, we find that the number of FinTech ETFs surges when investor sentiment toward FinTech is high. On average, 34% of FinTech ETFs engage in “FinTech Washing," as evidenced by the low fraction of FinTech stocks in their portfolios and low risk-exposure to the FinTech space. Despite their high fees (68 bps per annum), FinTech ETFs yield annual excess returns of -13%, significant even after accounting for various risk factors. The investor base, primarily comprised of retail investors, is not aware of the FinTech washing and appears unresponsive to unsatisfactory performance. Their underperformance can be attributed to market timing and the activeness of funds. The disappointing performance cannot be explained by low-quality fund families launching those ETFs. Overall, the evidence suggests that asset managers capitalize on the retail investors' sentiment toward the FinTech space by offering misrepresented and low-quality ETFs, which carries significant policy and welfare implications for both regulators and investors.
How Does Soft Information Affect External Firm Financing? Evidence from Online Employee Ratings, 2020
(with Thomas Chemmanur and Harshit Rajaiya)
Conference: EFA, MFA, Boca Corporate Finance and Governance Conference | Media coverage: Columbia Law School’s Blue Sky Blog
Abstract: We analyze how employees’ online ratings of firms’ affect their corporate financing and investment policies. We hypothesize that, while employees are unlikely to have access to inside information, their ratings, being driven by their day-to-day interactions with their employers, are likely to be correlated with long-run firm value and performance. This means that employee ratings are likely to affect the external financing behavior of firms in a setting where potential equity investors have access to online employee ratings (and firm insiders are aware of such access). We develop and test hypotheses based on the above assumptions using a large sample of around 1.1 million employee ratings from the Glassdoor website covering a sample of 2842 public firms. We find that firms with higher average online employee rating realizations are associated with algebraically greater abnormal stock returns upon an equity issue announcement; a greater propensity to have positive abnormal stock returns upon such an announcement; a greater propensity to issue equity rather than debt to raise external financing; higher annual investment expenditures; greater participation by institutional investors in their equity offerings (SEOs); and better long-run post-SEO operating performance. We demonstrate causality by making use of a difference-in-differences (DID) methodology relying on the staggered implementation of laws protecting the First Amendment Rights of citizens (anti-SLAPP laws) across US states.
The Real Effects of Government Intervention: Firm-level Evidence from TARP, 2021
Conference: AEA Poster, NFA, Econometric Society Summer Meeting.
Abstract: This paper investigates the real and financial effects of the largest government intervention in US history, the Troubled Asset Relief Program (TARP), on individual firms. Firms borrowing from banks that participate in TARP increase long-term debt and have more cash holdings and working capital after the Program compared to firms borrowing from banks that do not participate in TARP. But, there is no significant impact of TARP on corporate investment, employment, or R&D. We conclude that TARP exerts significant influence on firms’ liquidity and financial decisions, yet its impact on firms’ real activities is limited.
Work in progress
Work in progress
Abstract: We examine what drives attention to mutual fund disclosures, as well as its implication for fund future flow and performance.
FOMC Announcements, Short Selling, and Anomalies
(with Zhi Da, Xi Dong and Yushui Shi)
Conferences: AEA Poster, Hedge Fund and Private Equity Research Conference
Abstract: We examine short selling activities around FOMC announcements and its implications for anomalies.
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