Investor Sentiment and the Cross‐Section of Stock Returns
Open accessAbstract
We study how investor sentiment affects the cross‐section of stock returns. We predict that a wave of investor sentiment has larger effects on securities whose valuations are highly subjective and difficult to arbitrage. Consistent with this prediction, we find that when beginning‐of‐period proxies for sentiment are low, subsequent returns are relatively high for small stocks, young stocks, high volatility stocks, unprofitable stocks, non‐dividend‐paying stocks, extreme growth stocks, and distressed stocks. When sentiment is high, on the other hand, these categories of stock earn relatively low subsequent returns.
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DeepSeek news signals are highly correlated with the investor sentiment measure proposed by Baker and Wurgler (2006).
“A detailed examination further indicates that these news signals are highly correlated with the investor sentiment measure proposed by Baker and Wurgler (2006), whereas sentiment metrics extracted via GPT do not display a statistically significant correlation with investor sentiment.”
From ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy? (2025) · cites this paper as Baker and Wurgler (2006)
Sentiment metrics extracted via GPT do not display a statistically significant correlation with investor sentiment.
“A detailed examination further indicates that these news signals are highly correlated with the investor sentiment measure proposed by Baker and Wurgler (2006), whereas sentiment metrics extracted via GPT do not display a statistically significant correlation with investor sentiment.”
From ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy? (2025) · cites this paper as Baker and Wurgler (2006)
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Cites
Common risk factors in the returns on stocks and bonds
Fama, E. F., & French, K. R. (1993) · Journal of Financial Economics · doi:10.1016/0304-405x(93)90023-5 · Cited by 25,754 · see citing works
Public Regulation of the Securities Markets
Stigler, G. J. (1964) · The Journal of Business · doi:10.1086/294677 · Cited by 679 · see citing works
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Research works printed but not linked: 65
- Amihud, Yakov, and Haim Mendelson, 1986, Asset pricing and the bid-ask spread, Journal of Financial Economics 17, 223-249.
- Asness, Clifford S., Jacques A. Friedman, Robert J. Krail, and John M. Liew, 2000, Style timing: Value versus growth, Journal of Portfolio Management 26, 50-60.
- Baker, Malcolm, and Jeremy Stein, 2004, Market liquidity as a sentiment indicator, Journal of Financial Markets 7, 271-299.
- Baker, Malcolm, and Jeffrey Wurgler, 2000, The equity share in new issues and aggregate stock returns, Journal of Finance 55, 2219-2257.
- Baker, Malcolm, and Jeffrey Wurgler, 2004, A catering theory of dividends, Journal of Finance 59, 1125-1165.
- Banz, Rolf, 1981, The relationship between return and market value of common stocks, Journal of Financial Economics 9, 3-18.
- Barberis, Nicholas, and Andrei Shleifer, 2003, Style investing, Journal of Financial Economics 68, 161-199.
- Barberis, Nicholas, Andrei Shleifer, and Jeffrey Wurgler, 2005, Comovement, Journal of Financial Economics 75, 283-318.
- Barry, Christopher B., and Stephen J. Brown, 1984, Differential information and the small firm effect, Journal of Financial Economics 13, 283-294.
- Benveniste, Lawrence M., Alexander P. Ljungqvist, William J. Wilhelm, Jr., and Xiaoyun Yu, 2003, Evidence of information spillovers in the production of investment banking services, Journal of Finance 58, 577-608.
- Blume, Marshall, and Robert Stambaugh, 1983, Biases in computed returns: An application to the size effect, Journal of Financial Economics 12, 387-404.
- Brown, Gregory W., and Michael T. Cliff, 2004, Investor sentiment and the near-term stock market, Journal of Empirical Finance 11, 1-27.
- Brown, John Dennis, 1991, 101 Years on Wall Street (Prentice Hall, Englewood Cliffs, NJ).
- Brunnermeier, Markus, and Lasse Pedersen, 2005, Predatory trading, Journal of Finance 60, 1825- 1863.
- Campbell, John Y., and John H. Cochrane, 2000, Explaining the poor performance of consumption- based asset pricing models, Journal of Finance 55, 2863-2878.
- Chan, Louis K.C., Jason Karceski, and Josef Lakonishok, 2000, New paradigm or same old hype in equity investing? Financial Analysts Journal 56, 23-36.
- Cochrane, John H., 2003, Stocks as money: Convenience yield and the tech-stock bubble, in William C. Hunter, George G. Kaufman, and Michael Pomerleano, eds.: Asset Price Bubbles (MIT Press, Cambridge).
- D'Avolio, Gene, 2002, The market for borrowing stock, Journal of Financial Economics 66, 271-306.
- Daniel, Kent, and Sheridan Titman, 1997, Evidence on the characteristics of cross-sectional vari- ation in stock returns, Journal of Finance 46, 1739-1764.
- De Long, J. Bradford, Andrei Shleifer, Lawrence H. Summers, and Robert Waldmann, 1990, Noise trader risk in financial markets, Journal of Political Economy 98, 703-738.
- Duffie, Darrell, Nicolae Garleanu, and Lasse H. Pedersen, 2002, Securities lending, shorting, and pricing, Journal of Financial Economics 66, 307-339.
- Elton, Edwin J., Martin J. Gruber, and Jeffrey A. Busse, 1998, Do investors care about sentiment?, Journal of Business 71, 477-500.
- Fama, Eugene F., and Kenneth R. French, 1992, The cross-section of expected stock returns, Journal of Finance 47, 427-465.
- Fama, Eugene F., and Kenneth R. French, 2001, Disappearing dividends: Changing firm charac- teristics or lower propensity to pay? Journal of Financial Economics 60, 3-44.
- Geczy, Christopher C., David K. Musto, and Adam V. Reed, 2002, Stocks are special too: An analysis of the equity lending market, Journal of Financial Economics 66, 241-269.
- Gomes, Joao, Leonid Kogan, and Lu Zhang, 2003, Equilibrium cross section of returns, Journal of Political Economy 111, 693-732.
- Gruber, Martin J., 1966, The determinants of common stock prices, Ph.D. dissertation, Columbia University.
- Hausch, Donald, and William Ziemba, 1995, Efficiency of sports and lottery betting markets, In: Handbooks in Operations Research and Management Science, Volume 9, Elsevier, New York, NY.
- Ibbotson, Roger, and Jeffrey F. Jaffe, 1975, 'Hot issue' markets, Journal of Finance 30, 1027-1042.
- Ibbotson, Roger, Jody Sindelar, and Jay Ritter, 1994, The market's problems with the pricing of initial public offerings, Journal of Applied Corporate Finance 7, 66-74.
- Jones, Charles, and Owen Lamont, 2002, Short sale constraints and stock returns, Journal of Financial Economics 66, 207-239.
- Keim, Donald, 1983, Size-related anomalies and stock return seasonality: Further empirical evi- dence, Journal of Financial Economics 12, 13-32.
- Kothari, S. P., and Jay Shanken, 1997, Book-to-market, dividend yield, and expected market re- turns: A time-series analysis, Journal of Financial Economics 44, 169-203.
- Kindleberger, Charles, 2001, Manias, Panics, and Crashes (Wiley, New York).
- La Porta, Rafael, Josef Lakonishok, Andrei Shleifer, and Robert W. Vishny, 1997, Good news for value stocks: Further evidence on market efficiency, Journal of Finance 52, 859-874.
- Lakonishok, Josef, and Inmoo Lee, 2001, Are insider trades informative?, Review of Financial Studies 14, 79-111.
- Lakonishok, Josef, Andrei Shleifer, and Robert W. Vishny, 1994, Contrarian investment, extrapo- lation, and risk, Journal of Finance 49, 1541-1578.
- Lamont, Owen A., and Richard H. Thaler, 2003, Can the market add and subtract? Mispricing and tech stock carve-outs, Journal of Political Economy 111, 227-268.
- Lancaster, Kelvin J., 1966, A new approach to consumer theory, Journal of Political Economy 74, 132-157.
- Lee, Charles, Andrei Shleifer, and Richard H. Thaler, 1991, Investor sentiment and the closed-end fund puzzle, Journal of Finance 46, 75-109.
- Lettau, Martin, and Sydney Ludvigson, 2001, Resurrecting the (C)CAPM: A cross-sectional test when risk premia are time-varying, Journal of Political Economy 109, 1238-1287.
- Ljungqvist, Alexander, and William Wilhelm, 2003, IPO pricing in the dot-com bubble, Journal of Finance 58, 723-752.
- Loughran, Tim, and Jay Ritter, 1995, The new issues puzzle, Journal of Finance 50, 23-51.
- Lowry, Michelle, and G. William Schwert, 2002, IPO market cycles: Bubbles or sequential learning?, Journal of Finance 57, 1171-1200.
- Markowitz, Harry, 1959, Portfolio Selection: Efficient Diversification of Investments (Wiley, New York).
- Menzly, Lior, Tano Santos, and Pietro Veronesi, 2004, Understanding predictability, Journal of Political Economy 112, 1-47.
- Mitchell, Mark L., Todd Pulvino, and Erik Stafford, 2002, Limited arbitrage and equity markets, Journal of Finance 57, 551-584.
- Neal, Robert, and Simon Wheatley, 1998, Do measures of investor sentiment predict stock returns, Journal of Financial and Quantitative Analysis 34, 523-547.
- Ofek, Eli, and Matthew Richardson, 2002, DotCom mania: The rise and fall of internet stocks, Journal of Finance 58, 1113-1138.
- Reinganum, Marc R., 1983, The anomalous stock market behavior of small firms in January: Empirical tests for tax-loss selling effects, Journal of Financial Economics 12, 89-104.
- Ritter, Jay, 1984, The 'hot issue' market of 1980, The Journal of Business 57, 215-240.
- Ritter, Jay, 1991, The long-run performance of initial public offerings, Journal of Finance 46, 3-27.
- Seyhun, H. Nejat, 1998, Investment Intelligence from Insider Trading (MIT Press, Cambridge).
- Shiller, Robert J., 1981, Do stock prices move too much to be justified by subsequent changes in dividends? American Economic Review 71, 421-436.
- Shleifer, Andrei, 2000, Inefficient Markets (Oxford UP, Oxford).
- Shleifer, Andrei, and Robert W. Vishny, 1997, The limits of arbitrage, Journal of Finance 52, 35-55.
- Siegel, Jeremy, 1998, Stocks for the Long Run (McGraw-Hill, New York).
- Smith, E. E., E. J. Shoben, and L. J. Rips, 1974, Structure and process in semantic memory: A featural model for semantic decisions, Psychological Review 81, 214-241.
- Speiss, D. Katherine, and John Aff leck-Graves, 1995, Underperformance in long-run stock returns following seasoned equity offerings, Journal of Financial Economics 38, 243-267.
- Spiess, Katherine, and John Aff leck-Graves, 1999, The long-run performance of stock returns following debt offerings, Journal of Financial Economics 54, 45-73.
- Stambaugh, Robert F., 1999, Predictive regressions, Journal of Financial Economics 54, 375-421.
- Swaminathan, Bhaskaran, 1996, Time-varying expected small firm returns and closed-end fund discounts, Review of Financial Studies 9, 845-887.
- Wachter, Jessica, 2000, Habit formation and the cross-section of asset returns, Chapter 4 of Ph.D. dissertation, Harvard University.
- Wurgler, Jeffrey, and Katia Zhuravskaya, 2002, Does arbitrage f latten demand curves for stocks?, Journal of Business 75, 583-608.
- Zweig, Martin E., 1973, An investor expectations stock price predictive model using closed-end fund premiums, Journal of Finance 28, 67-87.
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- Authors
- BAKER, M., & WURGLER, J.
- Affiliations
- National Bureau of Economic Research (US)
- ORCID
- WURGLER, JEFFREY
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2006-08
- Volume
- 61
- Issue
- 4
- Pages
- 1645-1680
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W3121467893
- Cited by
- 6,049
- References
- 2
- Citations by year
- 2026: 500 · 2025: 586 · 2024: 524 · 2023: 522 · 2022: 500 · 2021: 521 · 2020: 417 · 2019: 355 · 2018: 347 · 2017: 280 · 2016: 263 · 2015: 241 · 2014: 214 · 2013: 176 · 2012: 164
- FWCI
- 99.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Journal of Finance (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Business, Management and Accounting › Accounting › Financial Analysis and Corporate Governance
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
- Keywords
- investor sentiment, cross-section of stock returns, subjective valuation, arbitrage, small stocks, young stock, growth stocks
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