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Can analysts predict rallies better than crashes?

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  • Medovikov, Ivan

Abstract

We use the copula approach to study the structure of dependence between sell-side analysts’ consensus recommendations and subsequent security returns, with a focus on asymmetric tail dependence. We match monthly vintages of I/B/E/S recommendations for the period January–December 2011 with excess security returns during six months following recommendation issue. Using a mixed Gaussian–symmetrized Joe–Clayton copula model we find evidence to suggest that analysts can identify stocks that will substantially outperform, but not underperform relative to the market, and that their predictive ability is conditional on recommendation changes.

Suggested Citation

  • Medovikov, Ivan, 2014. "Can analysts predict rallies better than crashes?," Finance Research Letters, Elsevier, vol. 11(4), pages 319-325.
  • Handle: RePEc:eee:finlet:v:11:y:2014:i:4:p:319-325 DOI: 10.1016/j.frl.2014.08.001
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    References listed on IDEAS

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    Cited by:

    1. Roger, Tristan, 2017. "Reporting errors in the I/B/E/S earnings forecast database: J. Doe vs. J. Doe," Finance Research Letters, Elsevier, pages 170-176.

    More about this item

    Keywords

    Analyst recommendations; Copulas; Non-linear dependence;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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