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1 January 2014 CFA Institute Journal Review

Bucking the Trend: The Informativeness of Analyst Contrarian Recommendations (Digest Summary)

  1. Keith Joseph MacIsaac, CFA, CIPM

Market participants attach greater significance to analysts’ contrarian recommendations than to trending recommendations because they perceive contrarian recommendations as more likely to contain private information. Furthermore, contrarian revisions are more likely to be issued by all-star analysts and, paradoxically, less likely to be issued by experienced analysts.

What’s Inside?

The author examines the traditional view of analysts as conduits of insightful company information beyond the mere consensus. He focuses on analysts’ contrarian recommendations—that is, when the recommendation is inconsistent with a stock’s recent performance—because this action in itself requires autonomy. By carefully controlling for the presence of various confounding influences, the author is able to isolate the market response to contrarian recommendations and trending recommendations—that is, those that conform to recent stock performance. He finds that the immediate market response to contrarian revisions is 0.27% higher than the response to trending revisions for upgrades and 0.59% lower than the response to trending revisions for downgrades.

How Is This Research Useful to Practitioners?

Previous research and the author’s study agree that the market perceives contrarian recommendations to be more informative than trending recommendations, and this belief is reflected in significant stock price movement. But more recently, this conclusion has been challenged because of commingling effects that call into question the degree of analysts’ influence. The author addresses this concern by constructing the sample in such a way as to ensure it properly attributes the stock price impact of analysts’ recommendations, thereby reaffirming these assertions.

Because of the importance of contrarian recommendations, the author further explores their characteristics, focusing on the analyst, the companies analyzed, and the impact of regulations implemented during the research period. His findings are robust to controlling for company size and return reversals, demonstrating that the results are not biased by the tendency for smaller-capitalization stocks to outperform larger-capitalization stocks or by stock prices bouncing in the bid–ask spread. These results are most apparent in the period before Regulation Fair Disclosure, which became effective in October 2000 and prohibits selective information disclosure. Overall, the evidence is most supportive of the view that contrarian revisions reflect private information; they are more likely to be issued by all-star analysts but less likely to be issued by analysts covering many firms and, surprisingly, analysts who are more experienced.

The author’s research clearly indicates that markets recognize analysts’ tendency to congregate around the consensus view and to issue upwardly biased recommendations. This tendency is, in part, the result of convincing evidence that analysts prefer momentum stocks. The author bypasses this debate by focusing on the immediate response to analysts’ contrarian recommendations rather than the ensuing longer-term performance, hence creating another opportunity for analysts to add value to markets.

How Did the Author Conduct This Research?

The final sample includes 53,085 recommendation revisions from the period of 1994–2009. The author’s research focuses on analysts’ recommendations that run counter to the direction of recent significant stock price movement. The author defines stock price changes as significant “if the past 1-month return over the period ending a week prior to the issuance of the revision exceeds one standard deviation in return volatility” (p. 2). Return volatility is calculated over the 60 months ending just prior to the one-month return horizon used to measure the impact of contrarian recommendations and is market adjusted to isolate a stock’s idiosyncratic volatility.

Analysts’ recommendations are classified into three groups based on the stock’s previous performance: contrarian, trending, or undetermined. Upgrade recommendations have to be either “buy” or “strong buy,” and downgrade recommendations have to be either “sell” or “strong sell.” These categories help distinguish bold revisions from those that are the result of herding. The author implements several other data controls and measurement conventions to ensure the sample is constructed to assess the information content only of analysts’ revisions.

The research is framed by three hypotheses—the private information hypothesis, the reluctance hypothesis, and the conflict hypothesis—to help explain market reactions to contrarian revisions. Each hypothesis is empirically tested, and the private information hypothesis (i.e., the market perceives that analysts’ contrarian revisions contain private information) emerges as the most consistent with the evidence.

Sell-side analysts’ stock recommendations and firms’ quarterly earnings during the period of January 1994–December 2012 are obtained from the Institutional Brokers’ Estimate System (I/B/E/S). Daily stock return data are from the Center for Research in Security Prices (CRSP). Firm-specific financial data are obtained from Compustat. All-star analysts’ data are from Institutional Investor’s annual research poll.

Abstractor’s Viewpoint

The author’s research highlights the conflict that can sometimes occur between human/corporate elements and the nuts-and-bolts quantitative analysis in analyst recommendations. This topic is timely given the current investigation by the New York State attorney general into efforts by buy-side firms to get advance notice of changes in analysts’ recommendations.

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