Analyst Recommendations Research Articles

Effects of managerial overconfidence on analyst recommendations

This study investigates the relation between managerial overconfidence and analyst recommendations. The empirical finding shows that analysts are less likely to issue upgrade recommendations for firms managed by overconfident CEOs. Similarly, analysts spend a longer time to upgrade stocks associated with overconfident CEOs. The effect of CEO overconfidence on recommendation revisions is non-monotonic. Analysts are more reluctant to upgrade firms with highly-overconfident CEOs. More experienced analysts are less susceptible to managerial overconfidence. Moreover, investors exhibit stronger response to recommendations for firms with overconfident CEOs.

Can Stock Analysts Predict Volatility?

We assess investment value of sell-side analyst recommendations from the standpoint of portfolio risk. We match I/B/E/S consensus recommendations issued for U.S.-listed equities during January 2015 with realized volatility of daily security returns up to one year following recommendation issue. Using a flexible semiparametric copula model we find recommendation levels to be associated with future changes in volatility, suggesting that analyst ratings can help manage portfolio risk. This relationship appears to be asymmetric and is most pronounced among the best-rated securities which experience largest volatility declines after recommendation issue. These effects are conditional on recommendation changes. We demonstrate that stock selection on the basis of such public recommendations can lead to a substantial reduction of portfolio value-at-risk.

Characteristic-Based Benchmark Returns and Corporate Events

We propose that fitted values from market-wide regressions of firm returns on lagged firm characteristics provide useful benchmarks for assessing whether average returns to certain stocks are abnormal. To illustrate, we study eight documented events with abnormal returns, including credit rating and analyst recommendation downgrades, initial and seasoned public equity offerings, mergers and acquisitions, dividend initiations, share repurchases, and stock splits. We show that the apparently abnormal returns in the months after these events are substantially reduced or eliminated when compared to characteristic-based benchmarks. Characteristic-based benchmarks perform better in explaining post-event returns than do recent four- and five-factor models. Received September 19, 2016; editorial decision February 16, 2018 by Editor Andrew Karolyi. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web Site next to the link to the final published paper online.

Do environmental-related disclosures help enhance investment recommendations?

PurposeUsing a sample of UK FTSE 350 companies continuously listed in the period 2007-2011, this paper aims to investigate the impact of the quality and quantity of corporate environmental disclosure on analysts’ recommendations.Design/methodology/approachThe study adopted a method based on that developed by Beck et al. (2010). The “CONI” approach measures information diversity, content and volume. It involves dual qualitative and quantitative measurement, which is suitable for the purpose of this paper.FindingsThe findings suggest that the quality of environmental disclosure is associated with more favourable buy recommendations. Mere volume of disclosure is insufficient for effective signalling about environmental strategies. Further tests show that only discretionary quality disclosure that is influenced by managerial intervention receives optimistic recommendation, suggesting that analysts are more likely to give better recommendation when managers have a higher level of discretion in their disclosures.Originality/valueThis paper contributes to the academic literature by empirically examining the association between sell-side analyst recommendations on both innate and discretionary components of environmental disclosures (quality and volume) within the UK context. This is a significant extension of the existing literature, which has focused on the related association between analyst recommendations and corporate social responsibility, mainly measured by corporate social responsibility ratings or a dummy variable reflecting the existence of supplementary corporate social responsibility reports in different international setting. The topic is of interest to contemporary accounting scholars and responds to calls for more research into how analysts use nonfinancial data such as environmental data in making recommendations.

The Accuracy of Analystss Recommendations on Malaysian Stock Prices

This study examines the price performance of Malaysian stocks recommended by the analysts of major stockbroking firms in Malaysia. Two questions are raised: whether investors can profit from the Malaysian stock market by following those analyst recommendations and whether buying (or selling) those recommended stocks could yield a higher return than the market during the same period of time. We conduct this research based on the information released by the major stockbroking firms, which were obtained from the popular blogs or websites providing information regarding market performance and target share prices in Malaysia. The samples period is in 2016, and a total of 139 recommendations issued by 9 professional Malaysian brokerage houses were identified. The performances of the recommended stocks were compared to the market returns based on one week (5 Days), three months, and six months after the trading recommendations were released. It is found that stocks covered by analysts, in general, outperformed the market as those stocks would usually draw the attention of the investors. The majority of the recommendations are favorable either in Buy or Hold categories. If investors follow the analysts’ recommendations to buy and sell, shareholders are likely to profit in the mid- to long-run and as compared to the benchmark index. However, the study does not find the evidence that the longer the duration, the price will converge more to the target prices. This study provides a novel attempt to assess to a certain extent, the institutional efficiency and the characteristics of the share market from the perspective of an emerging market.

Can Investors Profit from Security Analyst Recommendations?

This paper revisits the question of whether investors can benefit from consensus recommendations of stock market analysts in US equity markets. To examine the profitability net of transactions cost, we calculate transactions cost based on effective tick spread. We find that transactions cost becomes noticeably lower from 2001 and the strategy of purchasing 'strong buy' stocks and shorting 'strong sell' stocks yields the abnormal returns of 4.7-5.8% per year during the period of 2001-2016, even after accounting for transactions cost. We also find that 'strong buy (sell)' stocks are growth (value) firms and short-term winners (losers). We discuss our empirical results in the context of market efficiency.

Quiet Period Reit Returns

Executive SummaryExcess returns around the expiration of the IPO quiet period documented for industrial IPOs are minimal for REITs, supporting the argument that REITs are more transparent than other firms. The existence of analyst coverage impacts quiet period returns for REITs only during the pre-bubble period when coverage is less comprehensive. The frequency of analyst recommendations issued immediately after the quiet period for REITs is lower than for industrial IPOs, which again suggests greater REIT transparency since there is an implied lower need for coverage. Recommendations in number and in simple buy or sell categorization have a slight impact on returns. With marginal statistical significance, the small number of firms followed by four or more analysts posts excess returns while the very small number of firms with no buy recommendations posts negative excess returns.

How useful are the equity analysts' report? Evidence from Malaysia

Using 657 Malaysian sell-side analyst recommendations from January 2010 until December 2015, this paper documents the usefulness of equity analyst reports to investors. The research findings revealed that target price and earnings forecast had a significant association with stock return. However, trading volume was shown to have an insignificant relationship with the return. Overall, our results indicate that the information content in the analyst report contained only 66.67% explanatory vis a vis stock return and only target price and earnings forecast were useful. This paper is expected to add value in enriching the literature available on analyst report especially in the context of Malaysian market.

Case-based investing: Stock selection under uncertainty

Case-based decision theory (Gilboa and Schmeidler, 1995) predicts that given a new problem, a decision maker will act based on the memory of actions and outcomes in past similar situations. The concept of similarity plays a central role in explaining behavior. Unlike expected utility theory, case-based decision theory (CBDT) does not require a decision maker to know alternative courses of action or all possible outcomes associated with each action. Fitting a CBDT model to data on stock transactions of retail investors in the Philippines, the author analyzed whether past personal trading experience on a stock is applied to an objectively similar stock. Results show a significant similarity effect consistent with the prediction of CBDT. Past personal trading gains spillover to stocks within the same industry sector, which may preclude portfolio diversification. Investors also apply past outcomes on a recommended stock to similar stocks. This underscores the strong influence of analyst recommendation on investor decisions.

The Power of Firm Fundamentals in Explaining Stock Returns

Prior literature shows that earnings have come to explain less stock price movement over time, suggesting that firm fundamental information has become less important. In this paper, we replace earnings with earnings announcement returns as a measure of firm fundamental news and find that these firm fundamentals have come to explain more price movement over time. In the years after 2003, earnings announcement returns explain roughly 20% of the annual return—almost twice as much as they did before, indicating that fundamental information has become more important, not less, in explaining stock returns. This pattern occurs for other forms of firm fundamental information. Collectively, the returns around earnings announcements, management guidance, analyst forecasts, analyst recommendations, and 8-K filings went from explaining 17% of annual returns on average in the late 1990s to 39% on average in the early 2010s. In exploring possible explanations for the increase in the explanatory power of fundamental information, we find evidence consistent with regulatory changes, such as new 8-K filing requirements and Sarbanes-Oxley, collectively making disclosures more informative.

Can Investors Profit from Information Diversity?

There is heterogeneity in individual forecasts of any variable — inflation, corporate earnings, etc. The standard consensus estimate takes a simple average of individual forecasts, implicitly treating each forecast as a common signal plus noise. If some individuals know more than others, then a consensus estimate is not necessarily the optimal way to combine forecasts. I show how a recently developed statistical technique can infer overlap in information across agents and I apply it to stock recommendations of sell-side analysts. I find a trading strategy that delivers an alpha of 2-3% on an annualized basis, net of transaction costs, suggesting that information diversity is prevalent, economically significant, and tradable.

Are hated stocks good investments?

We study the performance of hated stocks, defined as stocks with the average analyst recommendation level of hold or worse. From 2009 to 2016, this group of hated stocks in S&P 500 performs better than the other stocks in S&P 500. When we extend the sample to all stocks with at least five analysts following, hated stocks again outperform non-hated stocks in the same time period. However, this result is driven by two factors: the impact of the time period of 2009 and 2010, and low priced stocks. If we start the strategy of investing in hated stocks at the beginning of 2011, or if we exclude low priced stocks, there is no significant outperformance of the hated stocks.

Appraisal Ratio and the Mutual Fund's Stock Picking Skill

According to the costly arbitrage theory, stocks with high idiosyncratic volatility deter arbitrageurs from trading against the temporal mispricing to gain profits. Hence, long equity holders, such as equity mutual funds, would not take on too much 'idiosyncratic risk' in their portfolios, unless they have strong beliefs that those assets are undervalued. In this study, we use the holding-based fund-level 'appraisal ratio', based on the Treynor and Black (1973) model, to infer the stock picking skill of actively managed mutual funds in the U.S. equity market. Overall, we find that the degree of a fund portfolio tilting towards stocks with higher 'appraisal ratio' helps to identify those funds with superior stock picking ability, which leads to better future performance. And the effect is stronger following periods with lower investor sentiment, indicating that this approach can identify those skilled fund managers who are active in terms of searching for undervalued stocks. Evidences from quarterly earnings announcements and analyst recommendations complement our conjecture that this measure is a good proxy for the stock picking ability of skilled fund managers in the U.S. active management industry.

Are analyst stock recommendation revisions more informative in the post‐IFRS period?

AbstractThis paper investigates whether the mandatory IFRS adoption has affected the informativeness of analyst recommendation revisions in Europe. Although prior studies document that IFRS adoption improved analyst forecast attributes, the impact of IFRS cannot be completely assessed without examining how the market reacts to information‐rich events in an environment with enhanced disclosure. To examine this question we utilize a difference‐in‐differences design using as main control sample firms that had voluntarily adopted IFRS before the EU's mandated switch. Overall, our evidence suggests that after the mandatory adoption of IFRS, both analyst upgrades and downgrades are more informative. These results hold after controlling for a number of variables that capture analyst, firm and information environment characteristics and are robust to a number of sensitivity analyses including the use of a US control sample. Finally, we examine whether our results are sensitive to the level of accounting enforcement. We find that analyst downgrades are more informative in the post‐IFRS period for firms in both high and low enforcement environments. Analyst upgrades, however, are more informative only if they are issued for firms in high enforcement countries.

How Is Earnings News Transmitted to Stock Prices?

We examine the speed and mechanism of the price discovery process following earnings announcements in the after-hours market, a very illiquid trading environment. Prices reflect earnings surprises mostly through changes in quotes rather than through trades. Following positive announcement surprises, ask prices adjust quickly while bid prices are slower to adjust, and vice versa for negative surprises. Returns computed from trade prices underestimate the speed and magnitude of price reactions following announcements relative to returns computed from quotes. These findings emphasize the importance of using quotes and not trade prices when examining intraday price discovery. Because firm announcements such as earnings generally occur in the after-hours market, using quotes is crucial as trading is sparse. We further illustrate the importance of quotes when examining the price discovery process around analyst recommendation revisions.

What Explains Herd Behavior in the Chinese Stock Market?

ABSTRACTThis article examines the causes of herd behavior in the Chinese stock market. Using the nonlinear model of Chang, Cheng, and Khorana [2000], the authors of this article find robust evidence of herding in both the up and down markets. They contribute to the existing literature by exploring the underlying reasons for herding in China. It is shown that analyst recommendation, short-term investor horizon, and risk are the principal causes of herding. However, the authors cannot find evidence that relates herding to firm size, nor can they detect significant differences in herding between state-owned enterprises and non–state-owned enterprises.

Firm reputation and investment decisions: The contingency role of securities analysts' recommendations

Moving beyond resource-based consequences of a firm's reputation, we develop a behavioral perspective on the impact of corporate reputation. Although there has been extensive discussion in previous studies of the benefits of reputation in terms of gaining resource advantages, we apply theory on self-regulatory focus to suggest that highly reputable firms may tend to have a prevention focus rather than a promotion focus in their investment strategies. This tendency will lead the firm to opt for low-risk investments rather than high-risk investments. Furthermore, we develop a contingency model and argue that the main effect of reputation on the investment decisions of the firm is further strengthened by the negative recommendations of securities analysts. We find support for our hypotheses. In doing so, we address emerging theories about the potential negative consequences of a firm's reputation and provide important insights for our theoretical understanding of the behavior of highly reputable firms.

Analyst ratings for firms filing for and reorganizing under Chapter 11

PurposeThe purpose of this paper is to examine analyst followings of firms starting from one year prior to their filing for Chapter 11 and as the firms progress through bankruptcy proceedings with a focus on firms receiving “Hold” or better recommendations. The authors attempt to answer questions such as what the common characteristics of the firms receiving stronger than expected recommendations one year prior to filing for bankruptcy reorganization or while in bankruptcy are, and how the market reacts to the issuance of stronger ratings for those firms.Design/methodology/approachThe authors design various regressions and apply them to a total of 2,754 sell-side analyst recommendations and 325 firms that are either approaching bankruptcy filing or in the process of reorganizing. In each analysis, the authors control for several firm and performance characteristics.FindingsThe authors find that the probability of securing stronger ratings is higher for small firms and for those followed by a greater number of analysts than for large firms and firms followed by fewer analysts. The market becomes more skeptical of optimistic evaluations closer to the date of bankruptcy filing (perhaps reflecting some anticipation) and reacts more positively to rating upgrades issued during bankruptcy protection than to the upgrades issued before the bankruptcy filing.Research limitations/implicationsThe conclusions are based on the analysis of analyst recommendations issued shortly before Chapter 11 filings and during bankruptcy proceedings. The conclusions could be strengthened by further analysis of firms’ post-bankruptcy recovery and performance and examination of analyst recommendations issued for the firms after they emerge from Chapter 11..Practical implicationsAnalyst security ratings that are more positive than expected are perhaps the result of superior expertise and access to private information. During bankruptcy proceedings, when information disclosure is limited, investors could greatly benefit from reports issued by security analysts.Originality/valueThis study contributes to the literature in a number of ways. First, the authors contribute to the literature on the analyst ratings of firms in distress by considering the period between bankruptcy filing and emergence, while the existing literature provides analysis of pre-bankruptcy recommendations and forecasts. Second, the authors focus on better than expected ratings rather than all types of ratings as the firms approach bankruptcy filings and proceed through reorganization. Finally, they evaluate how investors react to stronger than expected analyst ratings.

How Do Social Media Affect Analyst Stock Recommendations? Evidence from S&P 500 Electric Power Companies' Twitter Accounts

Research summary: The importance of firm‐stakeholder relationships is gaining increasing attention. Although a theory of the drivers and consequences of stakeholder pressure has been developing, it focuses on pressures from organized stakeholders such as shareholders, NGOs, and activists, and does not incorporate the emerging possibility that individual voices may matter. By exploring corporate Twitter, which facilitates movement of individual stakeholders such as customers to a higher stakeholder class by providing them with a greater sense of power and urgency, we study the circumstances under which customer voices significantly affect analyst stock recommendations. We find that favorable reactions to firm‐initiated messages matter, directly or indirectly, depending on the messages' growth implications. Customer‐initiated negative messages have a significant impact only with high volume and formal institutions that support customer opinions.Managerial summary: Social media is increasingly used by firms for disclosing information and engaging stakeholders. Yet, we know little about whether and how social media usage matters. We show how corporate Twitter usage may influence analyst stock recommendations. Our interviews of securities analysts suggest that social media is not institutionalized yet, but increasingly used as a source of channel checks, especially for vibes, validations, and so on. Our analyses of corporate Twitter accounts show that both firm‐initiated and customer‐initiated tweets can have significant impact on analyst recommendations under certain conditions. For firm‐initiated tweets, the extent of retweets is an important factor, along with the content of tweets, in particular, growth implications. For customer‐initiated tweets, negative tweets matter, but only with high volume and regulatory structure that supports customer protection. Copyright © 2017 John Wiley & Sons, Ltd.

Effects of ambiguity in market reaction to changes in stock recommendations

This study uses analyst recommendations and three ambiguity proxies, namely ambiguity in fundamentals, ambiguity in information and market ambiguity, to examine market reaction to recommendation changes in the Taiwanese stock market. The authors find that analysts’ recommendation changes have positive effects on subsequent buy-and-hold abnormal returns when market ambiguity is moderate. When ambiguity in fundamentals is low, recommendation changes have a positive influence on smaller firms. The effect of ambiguity in information on stock returns is associated with market ambiguity; market ambiguity is negatively associated with abnormal returns for firms with moderate ambiguity in fundamentals. Investors in a small firm rely more on analyst recommendations.