Abstract
This study elucidates how the distribution of stock recommendations influences brokerages’ revision strategies and investors’ response to the revisions. We first observe that brokerages tend to adopt mean reverting strategies when their current recommendation distribution deviates too much from their long-term mean buy ratio. However, this process is not straightforward, because brokerages adopt all buy- and sell-type strategies simultaneously. Further, we find that a “mean reverting” strategy for recommendation revisions provokes a less significant reaction from the market. In addition, any revision that enlarges the deviation results in a lower response because of the market’s suspicions of relative optimism or pessimism on the brokerage’s part. We conclude that a steady buy ratio is the best strategy for the brokerage to obtain most effective recommendation returns.
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Notes
A buy ratio refers to the composition of the buy recommendation contained in the quarterly overall recommendation distribution at the broker level.
Information on analysists research report, prior analyst recommendation literature and analyst recommendation data (mainly I/B/E/S), are merely focus on the sell-side analyst’s behavior (Groysberg et al. 2013; Jung et al. 2018). Roger (2017) points out that “To date, most empirical studies about sell-side financial analysts use the I/B/E/S database”. Therefore we employ the I/B/E/S database as our major source of dataset.
The industry coverage ratio is computed by dividing the number of firms in each industry the broker covered by the total number of companies the brokerage house covered.
Sell recommendations include sell and strong sell recommendations.
The market risk premium (Rm–Rf) is the return on NYSE/AMEX/NASDAQ value-weighted index (Rm) less the U.S. one-month T-bill rate (Rf).
We do not account for dropping the coverage of stocks because brokerages do not ordinarily disclose such news and identifying the exact date when analysts drop the coverage of the stocks is not easy when using I/B/E/S data.
We exclude the period from experience if a lapse of more than 182 days occurs before an analyst issues any forecasts. The experience continues to accumulate until the analyst’s forecasts appear on I/B/E/S.
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Lo, HC., Chan, CY. Mean reverting in stock ratings distribution. Rev Quant Finan Acc 60, 1065–1097 (2023). https://doi.org/10.1007/s11156-022-01121-4
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DOI: https://doi.org/10.1007/s11156-022-01121-4