IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-12-00924.html
   My bibliography  Save this article

Can analyst predict stock market crashes?

Author

Listed:
  • Terence t. l. Chong

    (Department of Economics and HK Institute of Asia-Pacific Studies, The Chinese Univ. of Hong Kong)

  • Xiaolei Wang

    (Department of Economics, The Chinese University of Hong Kong)

Abstract

The frequency of financial market turmoil has been rising over the past two decades. While the incidence of market turmoil has increased, the performance of analysts during tumultuous times has not received much attention in the literature. This paper examines whether the accuracy of analyst forecasts on stock returns varies during tumultuous times. Our results indicate that analysts' forecast performance during stock market crashes drops significantly.

Suggested Citation

  • Terence t. l. Chong & Xiaolei Wang, 2013. "Can analyst predict stock market crashes?," Economics Bulletin, AccessEcon, vol. 33(1), pages 158-166.
    • Handle: RePEc:ebl:ecbull:eb-12-00924
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2013/Volume33/EB-13-V33-I1-P15.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. 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.
    3. Peter D. Easton & Gregory A. Sommers, 2007. "Effect of Analysts' Optimism on Estimates of the Expected Rate of Return Implied by Earnings Forecasts," Journal of Accounting Research, Wiley Blackwell, vol. 45(5), pages 983-1015, December.
    4. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2002. "Breadth of ownership and stock returns," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 171-205.
    5. Qing He & Terence Tai‐Leung Chong & Li Li & Jun Zhang, 2010. "A Competing Risks Analysis of Corporate Survival," Financial Management, Financial Management Association International, vol. 39(4), pages 1697-1718, December.
    6. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    7. Adrian R. Pagan & Kirill A. Sossounov, 2003. "A simple framework for analysing bull and bear markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 23-46.
    8. Ajinkya, Bipin B & Gift, Michael J, 1985. "Dispersion of Financial Analysts' Earnings Forecasts and the (Option Model) Implied Standard Deviaitons of Stock Returns," Journal of Finance, American Finance Association, vol. 40(5), pages 1353-1365, December.
    9. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    10. Terence Tai-Leung Chong & Tau-Hing Lam, 2010. "Predictability of nonlinear trading rules in the U.S. stock market," Quantitative Finance, Taylor & Francis Journals, vol. 10(9), pages 1067-1076.
    11. 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.
    12. Robert M. Bushman & Joseph D. Piotroski & Abbie J. Smith, 2005. "Insider Trading Restrictions and Analysts' Incentives to Follow Firms," Journal of Finance, American Finance Association, vol. 60(1), pages 35-66, February.
    13. 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.
    14. repec:bla:jfinan:v:59:y:2004:i:5:p:1957-1978 is not listed on IDEAS
    15. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, February.
    16. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    17. Haiqiang Chen & Terence Tai‐Leung Chong & Zimu Li, 2011. "Are Chinese Stock Market Cycles Duration Independent?," The Financial Review, Eastern Finance Association, vol. 46(1), pages 151-164, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Terence Tai-Leung Chong & Xiaolei Wang, 2009. "The Nexus between Analyst Forecast Dispersion and Expected Returns Surrounding Stock Market Crashes," JRFM, MDPI, vol. 2(1), pages 1-19, December.
    2. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    3. Guo, Hui & Qiu, Buhui, 2014. "Options-implied variance and future stock returns," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 93-113.
    4. Turan G. Bali & Andriy Bodnaruk & Anna Scherbina & Yi Tang, 2018. "Unusual News Flow and the Cross Section of Stock Returns," Management Science, INFORMS, vol. 64(9), pages 4137-4155, September.
    5. Ling Cen & K. C. John Wei & Liyan Yang, 2017. "Disagreement, Underreaction, and Stock Returns," Management Science, INFORMS, vol. 63(4), pages 1214-1231, April.
    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. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    8. Nagel, Stefan, 2005. "Short sales, institutional investors and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 78(2), pages 277-309, November.
    9. Constantinos Antoniou & John A. Doukas & Avanidhar Subrahmanyam, 2016. "Investor Sentiment, Beta, and the Cost of Equity Capital," Management Science, INFORMS, vol. 62(2), pages 347-367, February.
    10. Zhong, Angel, 2018. "Idiosyncratic volatility in the Australian equity market," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 105-125.
    11. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2002. "Breadth of ownership and stock returns," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 171-205.
    12. Min, Byoung-Kyu & Qiu, Buhui & Roh, Tai-Yong, 2022. "What drives the dispersion anomaly?," Journal of Banking & Finance, Elsevier, vol. 138(C).
    13. Andreou, Christoforos K. & Lambertides, Neophytos & Panayides, Photis M., 2021. "Distress risk anomaly and misvaluation," The British Accounting Review, Elsevier, vol. 53(5).
    14. Chen, Lin & Qin, Lu & Zhu, Hongquan, 2015. "Opinion divergence, unexpected trading volume and stock returns: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 36(C), pages 119-127.
    15. Yu, Jialin, 2011. "Disagreement and return predictability of stock portfolios," Journal of Financial Economics, Elsevier, vol. 99(1), pages 162-183, January.
    16. Opie, Wei & Zhang, Hong Feng, 2013. "Investor heterogeneity and the cross-sectional stock returns in China," Pacific-Basin Finance Journal, Elsevier, vol. 25(C), pages 1-20.
    17. Qian, Xiaolin, 2014. "Small investor sentiment, differences of opinion and stock overvaluation," Journal of Financial Markets, Elsevier, vol. 19(C), pages 219-246.
    18. Jang, Jeewon & Kang, Jangkoo, 2019. "Probability of price crashes, rational speculative bubbles, and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 222-247.
    19. Jiang, Hao & Sun, Zheng, 2014. "Dispersion in beliefs among active mutual funds and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 114(2), pages 341-365.
    20. Chen, Honghui & Zheng, Minrong, 2021. "IPO underperformance and the idiosyncratic risk puzzle," Journal of Banking & Finance, Elsevier, vol. 131(C).

    More about this item

    Keywords

    Analyst forecast dispersion; Stock market crash; Excess returns.;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ebl:ecbull:eb-12-00924. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: John P. Conley (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.