Abstract
This study examines the performance of institutional trades in the context of recent analyst recommendation changes. We report several findings. First, institutional trades depend little on sell-side activity; they go against recent recommendation changes about as often as with them. Second, abnormal returns to institutional trading are negative, a finding consistent with the previous literature. Third, returns are most harmful when trades go against recent analyst recommendation changes. Fourth, institutional investment returns are still negative, but much less so, for trades that occur in quarters following no change in the consensus recommendation, yet are significantly positive for trades in accordance with previous recommendation changes. The difference in return between trades that agree with and trades that disagree with previous recommendation changes is 4–5.5% in the next quarter. Our results strongly suggest that institutional managers could increase their returns by merely following sell-side analysts' advice more often.
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Notes
We also use a more liberal 10% increase to proxy for seasoned equity offerings. This alternative cutoff does not materially affect our results. Because the performance of many institutions is benchmarked against stock market indices, part of the institutional trading in stocks may be explained by indexing. To remove the potentially confounding effect of indexing on our results, we eliminate all I(K,i,t) that are affected by additions and deletions to the S&P 500 index during the sample period. In order to do this we download a file that contains all additions and deletions to the S&P 500 index from Professor Jeffrey Wurgler’s website. This file also includes each stock’s company identifier, addition or deletion flag, and the announcement date and effective date for its addition to (or deletion from) the index, among other variables. If the institutional trading in a stock is related to that stock’s addition to (or deletion from) the S&P 500 index, we expect most of the trading to occur around the quarter of the addition/deletion. We determine the quarter and year of the addition or deletion for all stocks in this sample using the effective date and then merge it with our sample of stocks. We exclude from our sample all stock-quarters in which additions or deletions occurred.
We sincerely thank the referee for not only raising this excellent question but also guiding us to help answer the question.
We thank an anonymous referee for this suggestion.
We thank Brian J. Bushee for providing the classification data on institutional investors available at http://acct3.wharton.upenn.edu/faculty/bushee/IIvars.html.
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Appendix
Appendix
Past Return: Past return is the momentum variable. Following Jegadeesh and Titman (1993), each stock's momentum variable in a given month is defined as its buy and hold return over the past 6 months.
SIZE: SIZE is the stock's month-end market capitalization (price times shares outstanding).
Book-to Market: Book-to-Market is a firm's book-to-market ratio. We compute this ratio in month t of a year as the book value of equity ratio for the fiscal year ending in the prior fiscal year and market equity at the end of the month. The book value of equity is variable CEQ from COMPUSTAT annual files. Market equity is price time shares outstanding extracted from CRSP files.
Beta: We use the daily returns within a month to estimate stocks' beta and therefore employ the adjustment procedure of Scholes and Williams (1977) and Dimson (1979) to mitigate the impact of nonsynchronous trading. Beta is estimated using the following regression model:
where Ri,d, Rf,d, and Rm,d are the return on stock i on day d, the T-Bill return on day d, and the return on CRSP value-weighted market index on day d, respectively. The estimate of stock's beta is given by \( \overset{\lower0.5em\hbox{$\smash{\scriptscriptstyle\frown}$}}{\beta } _{i} = \overset{\lower0.5em\hbox{$\smash{\scriptscriptstyle\frown}$}}{\beta } _{{1,i}} + \overset{\lower0.5em\hbox{$\smash{\scriptscriptstyle\frown}$}}{\beta } _{{2,i}} + \overset{\lower0.5em\hbox{$\smash{\scriptscriptstyle\frown}$}}{\beta } _{{3,i}} \).
Illiquidity: Illiquidity is the measure of illiquidity for a stock in a given month. Following Amihud (2002), we measure Illiq as the ratio of stock's absolute monthly return to its dollar trading volume:
Coverage: Coverage is a measure of analyst coverage. The number of analysts following the firm in a month in the fiscal year, as reported in the IBES database summary files for annual earnings forecast.
Sales-Growth: Sales Growth is the ratio of past fiscal year sales to current year sales.
Volatility: Volatility is computed as the standard deviation of the past 12 months' return.
Price-Earning Ratio: Price-Earnings Ratio is the current closing month price extracted from CRSP files and past year earnings (EPSPX) taken from COMPUSTAT files.
Firm Age: number of months since the first return appears in the CRSP file.
Dividend Yield: cash dividends for the fiscal year ended before the most recent June 30, divided by size as of December 31 in that fiscal year.
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Hobbs, J., Singh, V. & Chakraborty, M. Institutional underperformance: Should managers listen to the sell-side before trading?. Rev Quant Finan Acc 57, 389–410 (2021). https://doi.org/10.1007/s11156-020-00948-z
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DOI: https://doi.org/10.1007/s11156-020-00948-z