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Incomplete information, idiosyncratic volatility and stock returns

  • Tony BERRADA

    (University of Geneva and Swiss Finance Institute)

  • Julien HUGONNIER

    (University of Lausanne and Swiss Finance Institute)

We develop a q-theoretic model of investment under incomplete information that explains the link between idiosyncratic volatility and stock returns. When calibrated to match properties of the US business cycles as well as various firms and industry characteristics, the model generates a negative relation between idiosyncratic volatility and stock returns. We show that conditional on earning surprises, the link is positive after good news and negative after bad news. This result provides new insights on the nature of stock return predictability.

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Paper provided by Swiss Finance Institute in its series Swiss Finance Institute Research Paper Series with number 08-23.

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Length: 49 pages
Date of creation: Jul 2008
Date of revision:
Handle: RePEc:chf:rpseri:rp0823
Contact details of provider: Web page: http://www.SwissFinanceInstitute.ch
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  1. Timmermann, Allan, 1996. "Excess Volatility and Predictability of Stock Prices in Autoregressive Dividend Models with Learning," Review of Economic Studies, Wiley Blackwell, vol. 63(4), pages 523-57, October.
  2. Tony Berrada, 2006. "Incomplete Information, Heterogeneity, and Asset Pricing," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 136-160.
  3. Timmermann, Allan G, 1993. "How Learning in Financial Markets Generates Excess Volatility and Predictability in Stock Prices," The Quarterly Journal of Economics, MIT Press, vol. 108(4), pages 1135-45, November.
  4. Longstaff, Francis A, 1989. " Temporal Aggregation and the Continuous-Time Capital Asset Pricing Model," Journal of Finance, American Finance Association, vol. 44(4), pages 871-87, September.
  5. Merton, Robert C., 1987. "A simple model of capital market equilibrium with incomplete information," Working papers 1869-87., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  6. Guo, Hui & Savickas, Robert, 2010. "Relation between time-series and cross-sectional effects of idiosyncratic variance on stock returns," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1637-1649, July.
  7. Pástor, Luboš & Veronesi, Pietro, 2002. "Stock Valuation and Learning about Profitability," CEPR Discussion Papers 3410, C.E.P.R. Discussion Papers.
  8. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
  9. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2008. "High Idiosyncratic Volatility and Low Returns: International and Further U.S. Evidence," NBER Working Papers 13739, National Bureau of Economic Research, Inc.
  10. Jonathan Berk & Richard C. Green & Vasant Naik, . "Optimal Investment, Growth Options and Security Returns," GSIA Working Papers 64, Carnegie Mellon University, Tepper School of Business.
  11. Lubos Pastor & Pietro Veronesi, 2009. "Learning in Financial Markets," NBER Working Papers 14646, National Bureau of Economic Research, Inc.
  12. Jiang, George J. & Xu, Danielle & Yao, Tong, 2009. "The Information Content of Idiosyncratic Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(01), pages 1-28, February.
  13. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2004. "The Cross-Section of Volatility and Expected Returns," NBER Working Papers 10852, National Bureau of Economic Research, Inc.
  14. Jonathan Lewellen & Jay Shanken, 2002. "Learning, Asset-Pricing Tests, and Market Efficiency," Journal of Finance, American Finance Association, vol. 57(3), pages 1113-1145, 06.
  15. Terence Lim, 2001. "Rationality and Analysts' Forecast Bias," Journal of Finance, American Finance Association, vol. 56(1), pages 369-385, 02.
  16. Bernard, Victor L. & Thomas, Jacob K., 1990. "Evidence that stock prices do not fully reflect the implications of current earnings for future earnings," Journal of Accounting and Economics, Elsevier, vol. 13(4), pages 305-340, December.
  17. Wei Huang & Qianqiu Liu & S. Ghon Rhee & Liang Zhang, 2010. "Return Reversals, Idiosyncratic Risk, and Expected Returns," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 147-168, January.
  18. Zhanhui Chen & Ralitsa Petkova, 2012. "Does Idiosyncratic Volatility Proxy for Risk Exposure?," Review of Financial Studies, Society for Financial Studies, vol. 25(9), pages 2745-2787.
  19. Steven R. Grenadier & Andrey Malenko, 2010. "A Bayesian Approach to Real Options: The Case of Distinguishing between Temporary and Permanent Shocks," Journal of Finance, American Finance Association, vol. 65(5), pages 1949-1986, October.
  20. Jouini, Elyès & Napp, Clotilde, 2007. "Consensus Consumer and Intertemporal Asset Pricing with Heterogeneous Beliefs," Economics Papers from University Paris Dauphine 123456789/78, Paris Dauphine University.
  21. Peterson, David R. & Smedema, Adam R., 2011. "The return impact of realized and expected idiosyncratic volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2547-2558, October.
  22. Clotilde Napp & Elyès Jouini, 2007. "Consensus consumer and intertemporal asset pricing with heterogeneous beliefs," Post-Print halshs-00152348, HAL.
  23. Chabi-Yo, Fousseni, 2011. "Explaining the idiosyncratic volatility puzzle using Stochastic Discount Factors," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1971-1983, August.
  24. Karl B. Diether & Christopher J. Malloy & Anna Scherbina, 2002. "Differences of Opinion and the Cross Section of Stock Returns," Journal of Finance, American Finance Association, vol. 57(5), pages 2113-2141, October.
  25. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
  26. Aydogan Alti, 2003. "How Sensitive Is Investment to Cash Flow When Financing Is Frictionless?," Journal of Finance, American Finance Association, vol. 58(2), pages 707-722, 04.
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