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To buy or not to buy? The value of contradictory analyst signals

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Abstract

We study the predictive ability of individual analyst target price changes for post-event abnormal stock returns within each recommendation category. Although prior studies generally demonstrate the investment value of target prices, we find that target price changes do not cause abnormal returns within each recommendation level. Instead, contradictory analyst signals (e.g., strong buy reiterations with large target price decreases) neutralize each other, whereas confirmatory signals reinforce each other. Further, our analysis reveals that large target price downgrades can be explained by preceding stock price decreases. However, upgrades are not preceded by stock price increases, thereby demonstrating asymmetric analyst behavior when adjusting target prices to stock prices. Our results suggest that investors should treat recommendations with caution when they are issued with large contradictory target price changes. Thus, instead of blindly following a recommendation, investors might put more weight on the change in the corresponding target price and consider transaction costs.

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Notes

  1. See, among others, Womack (1996); Barber et al. (2001); Jegadeesh et al. (2004); Green (2006), and Barber et al. (2009).

  2. See Brav and Lehavy (2003); Gleason et al. (2012); Huang et al. (2009), and Da and Schaumburg (2011). For an exhaustive literature review, we refer to Ramnath et al. (2008) and Bradshaw (2011).

  3. The stock price of Bank of America was approximately $7 in September 2011. Source of the analyst announcement: The Street (2011).

  4. See Thomson Reuters (2011).

  5. The average yearly return of the S&P 500 was 2.73 % from 2001 to 2007, 5.76 % from 1997 to 2004, and 25.73 % from 1997 to 1999.

  6. See Barber et al. (2006).

  7. In addition to this growing window approach, we calculate the results on a rolling window basis for the preceding year. The results are qualitatively the same but are slightly weaker.

  8. The heteroscedasticity problem, which might arise from the changing composition of the portfolios, as described in Mitchell and Stafford (2000), does not affect our conclusions for two reasons. For the portfolios from which we draw the main conclusions, heteroscedasticity seems implausible because the number of stocks in these portfolios is always high in terms of diversification (e.g., for the 1-month holding period, the average number of stocks per portfolio is approximately 170). Furthermore, we use heteroscedastic robust estimates.

  9. R\(_{j,t}\) is the return of portfolio \(j\) on day \(t\), R\(_{m}\) is the return on a value-weighted market portfolio, R\(_{f}\) is the 1-month Treasury bill rate, SMB is the return on a zero-investment portfolio calculated by the return on a portfolio consisting of small market capitalization stocks minus a portfolio of stocks with high market capitalization, HML is calculated by subtracting the return of a portfolio of low book-to-market stocks from a portfolio of high book-to-market stocks, and UMD is the return on a portfolio of stocks with high returns in the preceding year minus the return on a portfolio of stocks with low returns in the preceding year on day \(t.\) The factor-portfolio data are obtained from Kenneth French’s website.

  10. The literature identifies the highest post-event abnormal returns for recommendation changes representing strong new consistent information, such as upgrades to strong buy recommendations. See, for example, Womack (1996), Green (2006), and Barber et al. (2009).

  11. The stock assignments are obtained from Russ Wermers’s website. We also use these assignments to calculate the daily value-weighted return for each of the 125 benchmark portfolios. Delisting returns are taken into account as described on Russ Wermers’s website. See Daniel et al. (1997) and Wermers (2003).

  12. We choose to calculate both CARs and BHARs because both are subject to methodological concerns. See Barber and Lyon (1997) and Fama (1998).

  13. See Barber and Lyon (1997) for an empirical examination of this phenomenon.

  14. Transaction costs are higher for small stocks, and the influence on price of buying or selling large quantities of a stock is larger for small stocks. Assuming equal mis-valuations in the absence of arbitrageurs, Loughran and Ritter (2000) argue that mis-valuations in the presence of arbitrageurs, in equilibrium, must be larger for small stocks. Otherwise, arbitrageurs could make more money, net of costs, by finding mis-valuations among large stocks. See also Grossman and Stiglitz (1980), Pontiff (1996), and Shleifer and Vishny (1997).

  15. The least favorable portfolios assume a short position; thus, a trading profit is represented by positive values.

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Acknowledgments

We thank the seminar participants at the 2009 Midwest Finance Association Meeting, the 2009 Conference of the Swiss Society for Financial Market Research, and the 2009 Cologne Colloquium on Financial Markets. Moreover, we are grateful to Markus Schmid, the editor, and an anonymous referee for very helpful comments.

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Authors and Affiliations

  1. University of Cologne, Albertus Magnus Platz, 50923 , Cologne, Germany

    Stefan Kanne & Daniel Kreutzmann

  2. Cologne Graduate School (CGS), University of Cologne, Richard Strauss Strasse 2, 50931 , Cologne, Germany

    Jan Klobucnik

  3. Accounting Area, University of Cologne, Albertus Magnus Platz, 50923 , Cologne, Germany

    Soenke Sievers

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  1. Stefan Kanne
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  2. Jan Klobucnik
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Correspondence to Jan Klobucnik.

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Kanne, S., Klobucnik, J., Kreutzmann, D. et al. To buy or not to buy? The value of contradictory analyst signals. Financ Mark Portf Manag 26, 405–428 (2012). https://doi.org/10.1007/s11408-012-0196-z

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