Analyst Recommendation Changes Research Articles

Does online investor sentiment explain analyst recommendation changes? Evidence from an emerging market

PurposeThe authors examine how financial analysts respond to online investor sentiment when updating recommendations for specific stocks in South Africa. The aim is to establish whether online sentiment contains significant information that can influence analyst recommendations. The authors follow up the above by examining when online investor sentiment is most associated with analyst recommendation changes.Design/methodology/approachFor online investor sentiment proxies, the authors make use of the social media sentiment and news media sentiment scores provided by Bloomberg Inc. The sample size includes all companies listed on the Johannesburg Stock Exchange All Share Index. The study uses traditional ordinary least squares to examine the relation at the mean and quantile regression to identify the scope of the relationship across the distribution of the dependent variable.FindingsThe authors find evidence that pre-event news sentiment significantly influences analyst recommendation changes while no significant relationship is found with the Twitter sentiment. Further analysis shows that news sentiment is more influential when the recommendation changes are moderate (in the middle of the conditional distribution of the recommendation changes).Originality/valueThe study is the one of the first to examine the association between online sentiment and analyst recommendation changes in an emerging market using high frequency data. The authors also make a direct comparison between social media sentiment and news media sentiment, some of the most used contemporary investor sentiment proxies.

The Value of the Capital Market Development-Bursa Research Scheme's (CBRS) Recommendation Changes in

This study analyses the changes in analyst recommendations in the Malaysian stock market from 2010 to 2018. Using samples of 668 upgrade recommendations and 495 downgrade recommendations, this study employs event study methodology to examine price performance by predicting abnormal returns using the market model. The findings indicate that significant positive stock price reactions occur following upgrade recommendations and significant negative stock price reactions occur following downgrade recommendations over a short-term and up to six-month period. Further analysis reveals no statistically significant difference in performance between analysts who are participants of the Capital Market Development Fund – Bursa Research Scheme (CBRS) and those who are not. This finding implies that, despite the significant market reaction to both upgrade and downgrade recommendations, CBRS’s financial analysts do not provide better analysis than those of non-CBRS analysts.

Informational content of options around analyst recommendations

PurposeMore studies have investigated the relation between option measures and stock returns during scheduled corporate events. This study adds to the literature and investigates the informational role of options concerning stock returns following unscheduled corporate news events. The authors focus on individual analysts' recommendation changes rather than consensus revisions, as the recommendation consensus might discard a large amount of potentially valuable information in the aggregation process.Design/methodology/approachBased on the econometric model, the authors follow Bakshi et al. (2003) to construct the model-free option implied measures. The authors further decompose the implied option variance into upside and downside components. In such a way, the different informational roles of call and put options can be distinguished. A variety of regression analyses are conducted to examine the predictive power of option implied measures, and the ordered probit model is used to test the tipping hypothesis of analyst recommendations.FindingsThis study’s results show that the option market impounds the “valuable” firm-specific news; thus, the pre-event option market is strongly related to stock returns around recommendations even though recommendation changes are largely “unscheduled”. At the same time, these results suggest that upside (good) and downside (bad) implied volatilities contain distinctive information on subsequent stock returns.Originality/valueThis study provides new evidence that an increase in upside (downside) volatility around analyst recommendation changes would increase the probability that analysts upgrade (downgrade) the stock. The findings provide implications for investors and risk managers in making investment decisions.

The Role of Investor Sentiment and Valuation Uncertainty in the Changes around Analyst Recommendations: Evidence from U.S. Firms

The authors investigate the empirical relation among investor sentiment, valuation uncertainty, and announcements of changes in analyst recommendation decisions among U.S. firms. Recent behavioral finance evidence shows market sentiment to have predictive content that affects the classical relationship between analyst recommendations and stock return dynamics. Contrary to this evidence, the authors find that degree of valuation uncertainty is associated to the impact of investor sentiment when examining a likelihood of consensus recommendation upgrade or downgrade. While not totally eliminating the significant investor sentiment effect under high valuation uncertainty, the investor sentiment does not powerfully explain the stock market reactions to analyst recommendation changes under low valuation uncertainty. Furthermore, the authors show that analyst recommendations provide significant buy or sell signals if valuation uncertainty is great, referring to the market being highly competitive. However, in less competitive markets, analyst reports become less informative. Overall, the authors demonstrate that magnitude of valuation uncertainty is an important complement to investor sentiment for further understanding analyst recommendations.

Institutional underperformance: Should managers listen to the sell-side before trading?

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.

The Predictability of Future Aggregate Earnings Growth and the Relation between Aggregate Analyst Recommendation Changes and Future Returns

ABSTRACTWe extend prior research examining the relation between aggregate recommendation changes and future returns by documenting that this relation varies over time as a function of the predictability of future earnings growth. When industry-level earnings growth is more predictable, we find that recommendation changes relate negatively to future returns. Our evidence suggests that this negative relation results from analysts revising recommendations upward for higher expected earnings growth but failing to also adjust downward for a related decrease in expected returns arising from a decrease in investor risk aversion. In contrast, when industry-level earnings growth is less predictable, we find that recommendation changes relate positively to future returns. However, this positive relation results from analysts and investors similarly underestimating earnings growth persistence. Overall, the evidence fails to support the claim that analysts' recommendation changes incorporate aggregate information in a manner that adds value to investors by predicting future returns.JEL Classifications: A10; E10; E44; E52; G11; G14; M40; M41.

Is the Predictive Value of Analysts' Recommendations in Decline?: New Evidence from the U.S. Stock Market

Using 719,830 analyst recommendations from 1994 to 2017, we construct various portfolios based on levels and changes in analyst recommendations and examine how the value of those recommendations in predicting the abnormal stock returns has changed over time. We find that the predictive value of recommendations has been declining, especially after the implementation of NASD Rule 2711. More importantly, this decline in the predictive value results from the loss of its value in buy- and upgrade-related recommendations while sell- and downgrade-related ones are still associated with the negative abnormal returns. We also find a stronger relation between recommendations and stock returns in the post-Rule period. Our empirical results show that, in terms of stock returns, the Rule 2711 has mitigated the analysts’ conflicts of interest in stock recommendations.

Investor sentiment, stock returns, and analyst recommendation changes: The KOSPI stock market

ABSTRACTBy analysing daily data on the KOSPI stock market, we examine how investor sentiment and stock market returns respond to announcements of changes in analysts’ recommendations. In addition, we examine the effect of these announcements on the relationship between investor sentiment and stock returns. We find that investor sentiment is more sensitive to upgrade announcements than it is to downgrade announcements, implying that analyst reports yield meaningful trading indications to uninformed investors. Furthermore, investor sentiment becomes pessimistic prior to bad news being released, significantly affecting the response of stock returns to downgrade announcements. Thus, investor sentiment is one possible cause of asymmetric stock market reactions to changes in analysts’ recommendations.

Trading in the Presence of Short-Lived Private Information: Evidence from Analyst Recommendation Changes

We use a proprietary data set to test the implications of several asymmetric information models on how short-lived private information affects trading strategies and liquidity provision. Our identification rests on information acquisition before analyst recommendations are publicly announced. We provide the first empirical evidence supporting theoretical predictions that early-informed traders “sell the news” after “buying the rumor.” Further, we find distinct profit-taking patterns across different classes of institutions. Uninformed institutions, but not individuals, emerge as de facto liquidity providers to better-informed institutions. Placebo tests confirm that these trading patterns are unique to situations in which some investors have a short-lived informational advantage.

The effects of intraday news flow on dealers' quotations, market liquidity, and volatility

AbstractMarket regulators emphasize that the reduction in dealers' liquidity to today's markets is one of the drivers of extreme behaviour such as flash crash. Yet the challenge is to understand the effects of intraday news flow on dealers' quoting behaviour, high‐frequency returns, price volatility, liquidity, and trading activity. This paper addresses these issues shortly before the analyst recommendation changes on the Nasdaq. The sample period is 2004 at times where dealers were frequently displaying their quotations on the system. Results show that dealers remain active in quoting, in particular, in the events when the report is issued by their affiliated analysts. Their activity is associated with lower inside spreads, more trading, a more two‐sided market, and lower order imbalance.

Analyst recommendations and the implied cost of equity

We investigate the relation between analyst recommendations and the cost of equity implied by current stock price and earnings forecasts. Contrary to expectations, previous-year recommendation upgrades are associated with increases in the current cost of equity; and past increases in the cost of equity are associated with current recommendation downgrades. Furthermore, changes in the implied cost of equity and changes in analyst recommendations jointly explain as much as 31% of the variation in 1-year holding period returns, where most of the variation (28%) is explained by the implied cost of equity alone. We document that when forming recommendations, analysts underestimate the role of the cost of equity.

애널리스트 투자의견 변경 이전의 공매도거래에 대한 양방향 분석

애널리스트 투자의견 변경 이전의 공매도거래에 대한 양방향 분석

It Depends on Where You Search: Institutional Investor Attention and Underreaction to News

We propose a direct measure of abnormal institutional investor attention (AIA) using news searching and news reading activity for specific stocks on Bloomberg terminals. AIA is highly correlated with institutional trading measures and related to, but different from, other investor attention proxies. Contrasting AIA with retail attention measured by Google search activity, we find that institutional attention responds more quickly to major news events, leads retail attention, and facilitates permanent price adjustment. The well-documented price drifts following both earnings announcements and analyst recommendation changes are driven by announcements to which institutional investors fail to pay sufficient attention.Received February 24, 2016; editorial decision December 29, 2016 by Editor Andrew Karolyi.

Are Extended Hours Prices Predictive of Subsequent Stock Returns?

Trading outside the main session occurs between 4:00PM-8:00PM and 4:00AM-9:30AM and is typically dominated by institutional investors, as retail investors are discouraged to trade in the extended trading hours. This study examines whether trading in the extended hours is predictive of future returns. It shows that on regular trading days, extended hours returns are negatively associated with returns in the Main trading session (9:30AM-4:00PM), consistent with extended hours trading that is induced by liquidity needs rather than information. In contrast, when significant new information is released during the extended hours sessions such as earnings, analyst recommendation changes, and SEC filings, the extended hours returns are positively and significantly associated with the following Main session returns, and even with long-term drift returns. The evidence is consistent with an under-reaction to information on news days, and suggests that the return reaction during extended trading hours can help predict the return drift after news events.

Understanding the Direction, Magnitude, and Joint Effects of Reputation When Multiple Actors’ Reputations Collide

Despite extensive research efforts into the effects of reputation, virtually all of it has examined the effect of one type of reputation on one or more specific outcomes. But, how, for example, might the reputations of analysts, CEOs, and firms individually and jointly affect firm outcomes? To answer this question, the present study focuses on a context in which reputations are particularly relevant: changes in analyst recommendations and the effect of those changes on stock market reactions. Our study contributes to the increasing reputation literature by being one of the first to recognize and measure how the market accounts for multiple reputations. Further, we argue and find that the reputations of different actors interact with each other when determining particular firm outcomes. We also find that different actor’s reputations influence the reactions of observers.

Short sale constraints and information-driven short selling: evidence on NASDAQ

ABSTRACTThis article examines the impact of the NASDAQ’s bid test rule on the information content of short sales surrounding the U.S. Security Exchange Commission introduction of the pilot programme in 2005. It shows that abnormal short selling prior to analyst recommendation changes were very informative when stocks were restricted by the bid test rule. Such informativeness of short selling disappears when the bid test rule was temporarily suspended for pilot stocks. The results are robust after controlling for various factors that may contribute to this anomaly. Both the shorting efficiency hypothesis and the regulatory concern hypothesis are developed to provide explanations for this anomaly. Additional tests show that the regulatory concern is more consistent with the data.

It Depends on Where You Search: A Comparison of Institutional and Retail Attention

We propose a direct measure of abnormal institutional investor attention (AIA) at the daily frequency using the news-searching and news-reading activity for specific stocks on Bloomberg terminals. We find AIA to be highly correlated with measures of contemporaneous institutional trading, and related to but different from other investor attention proxies, including user requests at EDGAR which are limited to specific regulatory filings. Importantly, AIA enables us to directly contrast institutional attention with retail attention measured using Google search frequency. We find that institutional attention responds more quickly to major news events, triggers more trading, and is less constrained, compared to retail attention. In sharp contrast to retail attention which results in positive and temporary price pressure, AIA facilitates permanent price adjustment and alleviates price under-reaction to news. The well-documented price drifts following both earnings announcements and analyst recommendation changes come only from announcements where institutional investors fail to pay attention, according to our measure.

Why Do Options Prices Predict Stock Returns?

We use a new approach to assess the information transmission between options and stock markets. We study whether the predictive power of option-implied volatilities (IVs) on stock returns lies in analyst-related and/or earnings-related news. We find that two proxies for options trading (IV skew and IV spread) predict analyst recommendation changes, analyst forecast revisions, and earnings surprises. Next, we show that the IV skew and IV spread predict stock returns, and that the degree of predictability more than doubles around analyst-related and earnings-related events. Additionally, we find that informed traders choose to use the options market particularly because of short-sale constraints on the underlying stock. We also find that the informed options trading increases with the options market liquidity.

Two Worlds Colliding: Understanding the Effects of Reputational Domain Overlap

Despite the extensive research into the effects of reputation, virtually all of this research has examined the effect of one type of reputation on one or more specific outcomes. In this study we ask the question: How do the reputations of star analysts and star CEOs individually and jointly affect firm outcomes? To answer this question we focus on a context where reputations are particularly relevant – changes in analyst recommendations and the effect of those changes on stock market reactions. Our study makes a contributions to the growing reputation literature by being one of the first studies to recognize and measure how the market accounts for multiple reputations within a given context. Furthermore, we argue and find that the reputations of different actors interact with each other when determining particular firm outcomes. We find that different reputational domains influence both the actions of actors as well as the reactions of observers. Finally, we demonstrate that prior reputational research may have misstated the effects of reputation (either positively or negatively) by failing to consider how other forms of related reputation may jointly affect outcomes.

What Do Short Sellers Know?

Using a five-year panel of proprietary NYSE short sale order data, we investigate the sources of short sellers’ informational advantage. Heavier shorting is found the week before negative earnings surprises, analyst downgrades, and downward revisions in analyst earnings forecasts. The biggest effects are associated with analyst downgrades. While earnings and analyst event days constitute only 12% of sample days, they account for over 24% of the overall underperformance of heavily shorted stocks. The results are robust to factor timing and indicate that short sellers are well-informed about upcoming earnings news and are able to anticipate analyst recommendation changes. Shorting predictability is still significant after controlling for information in analyst actions, suggesting that short sellers know more than analysts about firm fundamentals. Finally, we find no evidence of price manipulation by short sellers.