By |Published On: January 20th, 2015|Categories: Research Insights, Behavioral Finance|

Stock Duration, Analysts Recommendations, and Misvaluation

  • Cremers, Pareek and Sautner
  • A version of the paper can be found here.
  • A blog on an older version of paper can be found here.
  • Want a summary of academic papers with alpha? Check out our Academic Research Recap Category.

Abstract:

This paper empirically studies how the interaction between short-term investors and analyst recommendations is related to a speculative component in stock prices. Using a new measure of the holding duration of institutional investors (called Stock Duration), we document that frequently traded stocks with optimistic (pessimistic) analyst recommendations have large negative (positive) future alphas that follow large positive (negative) past outperformance. Using Russell 2000 index reconstitutions to capture exogenous changes in institutional ownership, Stock Duration and analyst coverage, we conclude that strong analyst recommendations serve as a coordination mechanism among short-term, likely speculative, traders, causing significant misvaluations and subsequent price reversals.

Alpha Highlight:

Naïve investors are known as  uninformed, emotional, and often overly optimistic. That’s why the market needs professional, well-informed analysts who can help disseminate information and mitigate such speculator optimism. Sounds good. But is it possible this is just the professionals are bias as well?

Academic literature shows that analysts are biased and thus might exacerbate, rather than mitigate investor biases. If analysts themselves are affected by past price increases and their own overconfidence and make overly optimistic forecasts, speculative investors may in turn overreact to these forecasts, leading to additional buying, and sustained price momentum.

So, what role do analyst recommendations play?

This paper empirically tests whether analyst recommendations mitigate or aggravate the price impact of speculative trading. The paper finds support for the latter interpretation. When frequently traded stocks receive optimistic analyst recommendations, they tend to have large negative future alphas following large positive past outperformance!  Such price reversals only occur for stocks with two characteristics:

  1. are frequent traded
  2. have extreme analyst recommendations

The Two Main Components:

  • A Proxy for Short-term trading/frequent trading — Stock duration: calculated as the weighted-average length of time that institutional investors have held a stock in their portfolio. Put simply, it measures “how long a $1 investment in a stock has on average been in an institution’s portfolio at a particular point in time.” If stocks have decreased institutional holding durations, they are owned by new, possibly speculative investors.
  • Analyst recommendation: based on top and bottom quintile of the consensus or mean analyst recommendation. “A recommendation of 1 corresponds to “strong buy” and a recommendation of 5 corresponds to a “sell” recommendation.”

Key Findings:

  • In the first step, the paper sorts portfolios based only on Stock Duration. Table 2, Panel A shows that there is a positive relation between Stock Duration and future stock returns. Thus stocks with lower Stock Duration (decreasing institutional ownership), which are held by more short-term investors, are more likely to be misvalued.
2015-01-12 14_20_10-StockDurationAnalystsRecommendations_preview (1).pdf - Adobe Reader


The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

  • In the second step, the paper considers whether analyst recommendations mitigate or aggravate any price impact of speculative trading by short-term investors. In particular, the paper double sorts stocks on both Stock Duration and Mean Analyast Recommendation, and calculate subsequent holding returns for the next 12 months.
    • Results show that the value-weighted portfolio of stocks with short  stock duration and the most optimistic analyst recommendations has an annualized 5-factor alpha of -7.68% (-0.64%*12). On the contrary, the portfolio with short stock duration and the most pessimistic analyst recommendations has a 5-factor alpha of 6.48% per year (0.54%*12).
    • So a long-short portfolio that buy stocks in the latter and sell stocks in the former has an annualized 5-factor alpha of about 14.2%! Figure 2B shows the cumulative returns of this short duration long-short portfolio.
2015-01-12 13_38_05-StockDurationAnalystsRecommendations_preview (1).pdf - Adobe Reader


The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

  • Stocks with extreme analyst recommendations exhibit significant price reversals only if held by short-term investors (more likely to overreact). The figure below shows that short Stock Duration stocks with extreme recommendations encounter price reversal over the subsequent 2 years.
    • There is no price reversal of the past abnormal performance for the stocks with long Stock Duration.
2015-01-12 14_06_12-2015-01-12 11_11_42-StockDurationAnalystsRecommendations_preview (1).pdf - Adobe


The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

So what frictions prevent arbitrageurs from trading away these price reversals? The paper points out that there are “Limit of Arbitrage“. The paper uses idiosyncratic volatility, the short-interest ratio, and ownership by Dimensional Fund Advisers (DFA) to measure shorting costs. The paper finds that when shorting costs are high, the short Stock Duration stocks returns encounter larger negative returns.

About the Author: Wesley Gray, PhD

Wesley Gray, PhD
After serving as a Captain in the United States Marine Corps, Dr. Gray earned an MBA and a PhD in finance from the University of Chicago where he studied under Nobel Prize Winner Eugene Fama. Next, Wes took an academic job in his wife’s hometown of Philadelphia and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management firm dedicated to an impact mission of empowering investors through education. He is a contributor to multiple industry publications and regularly speaks to professional investor groups across the country. Wes has published multiple academic papers and four books, including Embedded (Naval Institute Press, 2009), Quantitative Value (Wiley, 2012), DIY Financial Advisor (Wiley, 2015), and Quantitative Momentum (Wiley, 2016). Dr. Gray currently resides in Palmas Del Mar Puerto Rico with his wife and three children. He recently finished the Leadville 100 ultramarathon race and promises to make better life decisions in the future.

Important Disclosures

For informational and educational purposes only and should not be construed as specific investment, accounting, legal, or tax advice. Certain information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed. Third party information may become outdated or otherwise superseded without notice.  Neither the Securities and Exchange Commission (SEC) nor any other federal or state agency has approved, determined the accuracy, or confirmed the adequacy of this article.

The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. Our full disclosures are available here. Definitions of common statistics used in our analysis are available here (towards the bottom).

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