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    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Barinov, Alexander 2015. Why does higher variability of trading activity predict lower expected returns?. Journal of Banking & Finance, Vol. 58, p. 457.

    Lerner, Peter 2015. Patience vs. impatience of traders: Formation of the value-at-price distribution through competition for liquidity. International Journal of Financial Engineering, Vol. 02, Issue. 03, p. 1550029.

    Sheng, Xuguang (Simon) and Thevenot, Maya 2015. Quantifying differential interpretation of public information using financial analysts’ earnings forecasts. International Journal of Forecasting, Vol. 31, Issue. 2, p. 515.

    Barinov, Alexander 2014. Turnover: Liquidity or Uncertainty?. Management Science, Vol. 60, Issue. 10, p. 2478.

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  • Journal of Financial and Quantitative Analysis, Volume 48, Issue 6
  • December 2013, pp. 1877-1900

Analyst Disagreement and Aggregate Volatility Risk

  • Alexander Barinov (a1)
  • DOI:
  • Published online: 20 February 2014

The paper explains why firms with high dispersion of analyst forecasts earn low future returns. These firms beat the capital asset pricing model in periods of increasing aggregate volatility and thereby provide a hedge against aggregate volatility risk. The aggregate volatility risk factor can explain the abnormal return differential between high- and low-disagreement firms. This return differential is higher for firms with abundant real options, and this fact can be explained by aggregate volatility risk. Aggregate volatility risk can also explain why the link between analyst disagreement and future returns is stronger for firms with high short-sale constraints.

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