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Institutional and individual sentiment: Smart money and noise trader risk?

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  • Schmeling, Maik

Abstract

Using a new data set on investor sentiment we show that institutional and individual sentiment proxy for smart money and noise trader risk, respectively. First, using bias-adjusted long-horizon regressions, we document that institutional sentiment forecasts stock market returns at intermediate horizons correctly, whereas individuals consistently get the direction wrong. Second, VEC models show that institutional sentiment forecasts mean-reversion whereas individuals forecast trend continuation. Finally, institutional investors take into account expected individual sentiment when forming their expectations in a way that higher (lower) expected sentiment of individuals lowers (increases) institutional return forecasts. Individuals neglect the information contained in institutional sentiment.
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  • Schmeling, Maik, 2007. "Institutional and individual sentiment: Smart money and noise trader risk?," International Journal of Forecasting, Elsevier, vol. 23(1), pages 127-145.
  • Handle: RePEc:eee:intfor:v:23:y:2007:i:1:p:127-145
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    1. Martin D.D. Evans & Richard K. Lyons, 2017. "Order Flow and Exchange Rate Dynamics," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 6, pages 247-290, World Scientific Publishing Co. Pte. Ltd..
    2. Peter Temin & Hans-Joachim Voth, 2004. "Riding the South Sea Bubble," American Economic Review, American Economic Association, vol. 94(5), pages 1654-1668, December.
    3. Honghui Chen & Gregory Noronha & Vijay Singal, 2004. "The Price Response to S&P 500 Index Additions and Deletions: Evidence of Asymmetry and a New Explanation," Journal of Finance, American Finance Association, vol. 59(4), pages 1901-1930, August.
    4. John M. Griffin & Jeffrey H. Harris & Selim Topaloglu, 2003. "The Dynamics of Institutional and Individual Trading," Journal of Finance, American Finance Association, vol. 58(6), pages 2285-2320, December.
    5. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    6. Chakravarty, Sugato, 2001. "Stealth-trading: Which traders' trades move stock prices?," Journal of Financial Economics, Elsevier, vol. 61(2), pages 289-307, August.
    7. Amihud, Yakov & Hurvich, Clifford M., 2004. "Predictive Regressions: A Reduced-Bias Estimation Method," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(4), pages 813-841, December.
    8. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    9. Frazzini, Andrea & Lamont, Owen A., 2008. "Dumb money: Mutual fund flows and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 88(2), pages 299-322, May.
    10. John Y. Campbell & Tarun Ramadorai & Tuomo O. Vuolteenaho, 2005. "Caught On Tape: Institutional Order Flow and Stock Returns," Harvard Institute of Economic Research Working Papers 2080, Harvard - Institute of Economic Research.
    11. Lu Zheng, 1999. "Is Money Smart? A Study of Mutual Fund Investors' Fund Selection Ability," Journal of Finance, American Finance Association, vol. 54(3), pages 901-933, June.
    12. Gregory W. Brown & Michael T. Cliff, 2005. "Investor Sentiment and Asset Valuation," The Journal of Business, University of Chicago Press, vol. 78(2), pages 405-440, March.
    13. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    14. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1413, August.
    15. Wang, Yaw-Huei & Keswani, Aneel & Taylor, Stephen J., 2006. "The relationships between sentiment, returns and volatility," International Journal of Forecasting, Elsevier, vol. 22(1), pages 109-123.
    16. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    17. Richard W. Sias, 2004. "Institutional Herding," Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 165-206.
    18. Simon Gervais & Ron Kaniel & Dan H. Mingelgrin, 2001. "The High‐Volume Return Premium," Journal of Finance, American Finance Association, vol. 56(3), pages 877-919, June.
    19. Philippe Bacchetta & Eric Van Wincoop, 2004. "A Scapegoat Model of Exchange-Rate Fluctuations," American Economic Review, American Economic Association, vol. 94(2), pages 114-118, May.
    20. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    21. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    22. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    23. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    24. John M. Griffin & Jeffrey H. Harris & Tao Shu & Selim Topaloglu, 2011. "Who Drove and Burst the Tech Bubble?," Journal of Finance, American Finance Association, vol. 66(4), pages 1251-1290, August.
    25. Cochrane, John H., 1991. "A critique of the application of unit root tests," Journal of Economic Dynamics and Control, Elsevier, vol. 15(2), pages 275-284, April.
    26. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1414, August.
    27. Sapienza, Paola & Polk, Christopher, 2003. "The Real Effects of Investor Sentiment," CEPR Discussion Papers 3826, C.E.P.R. Discussion Papers.
    28. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    29. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    30. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    31. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    32. Lee, Wayne Y. & Jiang, Christine X. & Indro, Daniel C., 2002. "Stock market volatility, excess returns, and the role of investor sentiment," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2277-2299.
    33. Neal, Robert & Wheatley, Simon M., 1998. "Do Measures of Investor Sentiment Predict Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(4), pages 523-547, December.
    34. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    35. John H. Boyd & Jian Hu & Ravi Jagannathan, 2005. "The Stock Market's Reaction to Unemployment News: Why Bad News Is Usually Good for Stocks," Journal of Finance, American Finance Association, vol. 60(2), pages 649-672, April.
    36. John Y. Campbell & Albert S. Kyle, 1993. "Smart Money, Noise Trading and Stock Price Behaviour," Review of Economic Studies, Oxford University Press, vol. 60(1), pages 1-34.
    37. John R. Nofsinger & Richard W. Sias, 1999. "Herding and Feedback Trading by Institutional and Individual Investors," Journal of Finance, American Finance Association, vol. 54(6), pages 2263-2295, December.
    38. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    39. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    40. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    41. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    42. S.G. Badrinath & Sunil Wahal, 2002. "Momentum Trading by Institutions," Journal of Finance, American Finance Association, vol. 57(6), pages 2449-2478, December.
    43. Glaser, Markus & Nöth, Markus & Weber, Martin, 2003. "Behavioral Finance," Sonderforschungsbereich 504 Publications 03-14, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    44. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    45. Bodurtha, James N, Jr & Kim, Dong-Soon & Lee, Charles M C, 1995. "Closed-End Country Funds and U.S. Market Sentiment," Review of Financial Studies, Society for Financial Studies, vol. 8(3), pages 879-918.
    46. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    47. Narasimhan Jegadeesh & Sheridan Titman, 2001. "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations," Journal of Finance, American Finance Association, vol. 56(2), pages 699-720, April.
    48. Jennifer Conrad & Bradford Cornell & Wayne R. Landsman, 2002. "When Is Bad News Really Bad News?," Journal of Finance, American Finance Association, vol. 57(6), pages 2507-2532, December.
    49. Valkanov, Rossen, 2003. "Long-horizon regressions: theoretical results and applications," Journal of Financial Economics, Elsevier, vol. 68(2), pages 201-232, May.
    50. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    51. Bange, Mary M., 2000. "Do the Portfolios of Small Investors Reflect Positive Feedback Trading?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(2), pages 239-255, June.
    52. Alok Kumar & Charles M.C. Lee, 2006. "Retail Investor Sentiment and Return Comovements," Journal of Finance, American Finance Association, vol. 61(5), pages 2451-2486, October.
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    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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