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By linking sell-side equity analysts to their deed records and LinkedIn profiles, I show that analysts with higher exposure to negative wealth shocks issue more pessimistic and less accurate forecasts. The effects are stronger when analysts have higher leverage in their homes and face career concerns. I also find that stocks recommended by exposed analysts underperform those of non-exposed counterparts, by an amount that is significant and economically large in magnitude. The results remain robust to unobserved skill differences, the potential endogeneity of housing prices, the self-selection of analysts into neighborhoods with certain traits, and placebo tests where housing wealth shocks are randomized across analysts. Collectively, this study provides new evidence on if and how personal wealth shocks impact analysts' work productivity and forecast behavior.

We examine how increased competition stemming from an innovation in financial technology influences sell-side analyst research quality. We find that firms added to Estimize, an open platform that crowdsources short-term earnings forecasts, experience a pervasive and substantial reduction in consensus bias and a limited increase in consensus accuracy relative to matched control firms. Long-term forecasts and investment recommendations remain similarly biased, alleviating the concern that the documented reduction in bias is a response to broad economic forces. At the individual analyst level, we find that bias reduction is more pronounced among close-to-management analysts, and that more biased analysts respond by reducing their coverage of Estimize firms. The collective evidence suggests that competition from Estimize improves sell-side research quality by discouraging strategic bias.

This paper extends qualitative research on sell-side analysts by investigating how analysts compete against each other in the market for investment advice. The paper challenges the assumption that ...

We examine institutional trading in relation to changes in consensus recommendations over time. We find that pre-Reg FD’s positive contemporaneous relation between hedge fund trading and change in consensus becomes negative after Reg FD, but the positive relation between non-hedge fund trading and change in consensus continues even after Reg FD. Furthermore, during post-Reg FD, while the performance of hedge funds’ trades that contradict with analysts improve, non-hedge funds’ trades that agree with analysts significantly deteriorate. Our evidence suggests that hedge funds have better information processing skill and are more cognizant about the role of selective information in analyst recommendations.

In this paper, we argue that when individual investors can obtain information from public resources such as Google search, the degree of investor attention to a particular underlying company is positively linked with herding behavior for retail investors. Empirical results confirm that Google Search Volume Index can be a proxy for the information demand of uninformed individual investors. Empirical evidence also shows that reaching the price limit generates an attention-grabbing effect. Further, in general, small cap firms generate more intensive individual investor herding. In addition, we explore the asymmetric impact of abnormal search volume index on individual investor herding behavior for bull and bear markets, and confirm that the individual investor buy herding phenomenon is stronger in bull markets, especially for small capitalization firms. In bear markets, with greater price deterioration for large cap firms, we detect herding behavior on the sell side.

The main objective of the paper is to investigate the analysts’ recommendations’ value and to determine on which market the analysts have more predictive power that can be defined as an extent of a stock price’s reaction around a particular recommendation what leads to abnormal returns of the security. Such recommendations are significant in decision‐making whether to buy or to sell a particular stock. We observed 1,881 events from 168 companies traded at the London Stock Exchange and the New York Stock Exchange in a period between January 1, 2016, and April 31, 2019. We used an event study analysis and classical one‐factor market model to determine expected returns for a particular stock in an estimation window. It was found that both American and European Union markets are feasible to be outperformed by the analysts but it is impossible to highlight any of the markets as they behave almost identically around positive, neutral and negative recommendations.

This paper uses a proprietary panel dataset to categorize and quantify the activities that sell-side brokerage analysts use to build and sustain their network of buy-side client relations. We then ...

Previous studies report a robust positive relationship between cash endowments and asset prices in experimental asset markets. Higher cash endowments generally increase the proportion of riskless versus risky wealth at the individual and aggregate level as well as the capacity of market participants to seize investment opportunities, i.e., their transactional liquidity. In this study, we vary the size and composition of riskless endowments in order to analyze the impact of different types of “cash” on trading behavior in experimental asset markets with randomly fluctuating fundamental values. In all treatments except the baseline, we allow subjects to control the liquidity of their cash endowment endogenously by providing some proportion of their riskless endowment in a physical store of value, which can be converted into experimental currency for trading. We observe that most subjects retain a large proportion of their wealth in the physical store of value. Inconsistent with rational choice theory, average trading prices and trading volumes are lower when “cash” is provided in a convertible store of value rather than experimental currency. Surprisingly, the price effect manifests asymmetrically on the buy side but not the sell side. Moreover, we control for potential changes in risk appetite resulting from higher riskless endowments. Our results suggest that transactional liquidity not a risky demand shift drives the relationship between cash endowments and asset prices.

This paper explores the ways in which sell‐side (SS) financial analysts seek to position themselves advantageously within the wider field of investment advice in spite of widespread skepticism over the value that their forecasts and recommendations add to investment decisions. The field of investment advice has been characterized in recent years by a number of regulatory and technological changes that have forced SS analysts to reconstitute the ways in which they influence the investment decisions of buy‐side (BS) actors. Faced with existential threats, SS analysts have responded to the disruptive impact of technology and regulation by struggling hard to ensure that their services are still valued by fund managers. Key to this ongoing process is the recalibration of professional expertise, which previous research has alluded to but not explored in detail. Central to the persistence of SS analysts in processes of investment decision making are activities revolving around the production and use of analyst reports which, our findings indicate, are less valuable for their informational content than their role as “relational devices,” ascribing legitimacy to SS analysts and earning them an entry ticket to more substantive, value‐adding interactions with companies and BS actors. We also show that economic considerations in the area of investment advice are influenced by social ties, the motivations of various actors in the field, and their relative position vis‐a‐vis other actors. More generally, we contribute to the literature on professional projects by showing how professional groups are constantly engaged in attempts to reposition themselves in the social space, but that field‐level changes can restrict the outcomes of these strategies to mitigation rather than advancement for the professionals concerned.

In this article, the authors posit a quid pro quo in economic benefits between sell-side equity analysts and large hedge fund managers. They show that large hedge funds opportunistically trade one to four days prior to the publication of a recommendation change, a finding consistent with flow of information from analysts to hedge funds. Next, the authors demonstrate that in return for the information provided, analysts benefit from (1) better external evaluations and (2) higher trading commissions and fees for their brokerage firm. Notably, pre-trading occurs only when the analyst issuing the recommendations has a high external evaluation and the analyst’s brokerage house is a prime broker to the hedge fund. TOPICS:Manager selection, fundamental equity analysis, portfolio construction

Between 2009 and 2013, the Fly on the Wall (FLY) leaked 58% of recommendation revisions with a median delay of 27 minutes relative to the IBES announcement time. We show that FLY improves price discovery, but leaked recommendations hamper brokers’ ability to offer price improvement on trades routed through them. Three major brokers sued FLY; using key court dates, we show significant wealth and real effects to the brokerage industry. Overall, the speed with which analyst recommendations are disseminated has led to more rapid price discovery at the expense of a decline in the scope of the sell-side research industry.

A number of sell-side healthcare analysts gain access to information outside the purview of management through Freedom of Information Act requests to the Food and Drug Administration for records on factory inspections, complaints, and drug and medical device applications. Using a difference-in-differences methodology, we find that buy (sell) recommendations and upgrades (downgrades) earn higher (lower) stock returns over the year following the receipt of FDA records. We also examine the type of information revealed in FDA factory inspection reports, and find that analysts are less likely to downgrade and are less pessimistic in their recommendations than the consensus recommendation when the information contained in the FDA report is not particularly severe. Our findings are consistent with a subset of analysts utilizing non-public information channels independent of management to gain value-relevant information about their covered firms.

Sell-side analysts employ different benchmarks when defining their recommendations. A buy for some brokers means the stock is expected to outperform its industry, while for other brokers, it means the stock is expected to outperform the market or some return threshold. We show that these stated benchmarks have implications for the distribution of recommendations, price reactions to recommendations, and the investment value of recommendations. We conclude that, depending on the question, academics may need to account for the benchmarks when studying analysts' outputs, and investors may find the benchmarks beneficial in interpreting analysts' advice. JEL Classifications: G10; G24.

Using a manually collected database of Shenzhen Stock Exchange listed firms from 2013 to 2015, we examine the key characteristics of firms’ private meetings and their effects on analysts’ reports. We show that the presence of managers, a smaller number of meeting participants, and discussing questions in more categories are associated with more accurate and less optimistic short-term forecasts during the hosting periods following the meeting. Our results suggest that private and small group conversations between managers and analysts can be significant information channels in these meetings. In particular, we show that the short-term earnings forecast is more accurate and less optimistic during hosting periods after these meetings in general, but recommendations are still biased upwardly. These results are robust regardless of whether the analyst attend meetings or whether the meeting is hold onsite, providing further evidence that private conversations with managers may be a more effective information channel than observing firms’ operations during site visits.

Mobilizing Foucault’s genealogy, this article investigates how an “ethics event”—the involvement by some sell-side financial analysts in the United States and United Kingdom across the past two decades in corporate governance—emerged. It is found that the complex relations formed between specific historical precedents, normative discourses, and fields of power rendered certain issues in financial markets morally problematic and constructed analysts’ corporate governance work as a potential solution. Contributing to research in finance ethics, this article develops a novel perspective to conceptualize the rise of ethically relevant practices in financial markets, focusing on how ethical problems and their solutions are outcomes of discursive construction and power relations. This article also revises our understanding of the boundary between technical norms and moral norms in financial markets. When ethical crises occur, it is argued, transforming technical practices and revising the technical norms adopted by financial professionals has the potential to tackle ethical concerns.

We measure the information content of publicly available analyst consensus forecasts for 1‐year‐forward earnings per share based on two well‐established price discovery measures drawn from the area of market microstructure research. Employing a 36‐year sample of large U.S. companies listed in the S&P 100 Index, we compute (a) Hasbrouck's information shares and (b) Gonzalo and Granger's common factor component shares to measure the relative contribution that market participants and financial analysts working on the sell side of the market have in the process of value discovery. We find that although these analysts are far from leading the market, they have a small but significant share in the process of value discovery, amounting to 4.6% (Hasbrouck) and 18.0% (Gonzalo and Granger), on average. This share is persistent over time but varies significantly in the cross section. We identify the level of analyst coverage and company age as drivers of this heterogeneity.

Because uncertainty is high in bad times, investors find it harder to assess firm prospects and hence should value analyst output more. However, higher uncertainty makes analysts’ tasks harder, so it is unclear whether analyst output is more valuable in bad times. We find that in bad times, analyst revisions have a larger stock‐price impact, earnings forecast errors per unit of uncertainty fall, and analyst reports are more frequent and longer. The increased impact of analysts is also more pronounced for harder‐to‐value firms. These results are consistent with analysts working harder and investors relying more on analysts in bad times.

We examine the effects the Chartered Financial Analyst® (CFA) designation program has on recommendation performance and career outcomes of the analysts who complete the CFA Program and become CFA charterholders. For these analysts, both their recommendation performance and their chances of making Institutional Investor’s All-America Research Team increased during the 1993–2015 period. These effects are attributable to the CFA Program curriculum. The results remain largely stable over the pre- and post-2000 subperiods, and they survive an array of robustness checks.

Equity analysts are often hired by firms they cover. I document the extent to which this revolving door phenomenon impairs analysts' independence. I do this by examining the presence of biased research reports issued during the year before analysts are employed by a firm they cover. I find that during their final year, revolving door analysts bias their EPS forecasts, their target prices, and their recommendations in a direction that suggests that they are attempting to gain favor from their prospective employers. Specifically, relative to other analysts, revolving door analysts issue more optimistic reports on the firms that hire them, and they issue more pessimistic reports on firms that do not hire them. These results suggest the presence of strategic bias, although more innocuous interpretations cannot be completely ruled out. JEL Classifications: G14; G17; G24; G28; M41. Data Availability: Data are available from public sources identified in the text.

We examine the participation of analysts from different buy-side institutions (hedge funds, mutual funds, and RIAs) in public earnings conference calls and the associated capital market implications. Using 81,652 conference call transcripts for 3346 companies from 2007 to 2016, we find that buy-side analysts ask questions on approximately 18% of calls. Relative to sell-side analysts, buy-side analysts' interactions with management are shorter, convey less favorable tone, and exhibit more uncertainty. Buy-side activity on earnings calls is also associated with subsequent reductions in sell-side coverage, and buy-side tone is associated with sell-side analysts' price target revisions after the call. Importantly, our findings suggest that buy-side analysts representing a hedge fund play an important and unique role on conference calls. Specifically, hedge fund analysts represent nearly half (47%) of all buy-side appearances. In addition, when short interest in the firm is high, analysts representing a hedge fund are less likely to be permitted to ask the first question on the call, to ask lengthy questions, or to ask additional follow-up questions. Relatedly, relative to other buy-side analysts, the information conveyed by hedge fund analysts during the call is more strongly associated with both stock returns and investor uncertainty following the call.

Between 1984 and 2014 over 3400 sell-side analysts changed the primary industry they followed. This article documents that analysts are more likely to change their industries when their absolute and relative forecasting accuracy in that industry is low and when the accuracy in the new industry is high. Analysts are more likely to switch industries at the beginning of their careers, after a recent change of an employing brokerage house, and if they have a history of switching industries before. Analysts are less likely to make a switch when their forecasting activity in the industry is high, when the industry is followed by many analysts and when they are employed by a top brokerage house.

We examine changes in the scope of the sell-side analyst industry and whether these changes impact information dissemination and the quality of analysts’ reports. Our findings suggest that changes in the number of analysts covering an industry impact analyst competition and have significant spillover effects on other analysts’ forecast accuracy, bias, report informativeness, and effort. These spillover industry effects are incremental to the effects of firm level changes in analyst coverage. Overall, a more significant sell-side analyst industry presence has positive externalities that can result in better functioning capital markets. This article is protected by copyright. All rights reserved

This study explores insider trading patterns under different earnings surprises. After controlling for stock market liquidity and earnings announcements returns, we show that insiders sell more aggressively depending on the heterogeneity of analysts whose EPS forecasts are met or beaten to camouflage their trades. Specifically, insiders sell more shares of their company sooner after the publication of earnings when top analysts' forecasts are met or beaten. Consistent with the informed trading literature, insiders strategically select these moments because the stock price impact is low and the legal scrutiny of their trades is minimal. To support this result, we employ an exogenous drop in firms' analyst coverage due to the closure or merger of brokerage houses. Furthermore, in line with the camouflage incentives, by selling after top analysts' forecasts are met or beaten, stock prices adjust slowly to insider trades. Finally, we show that the incentives of insiders to hide their trades are concentrated in opportunistic insiders and members of the top management team, who are more likely to bear the costs of selling shares after positive news.

We use daily page views of analyst estimates, ratings, and target prices on Yahoo Finance to understand when users seek sell-side analyst research. Demand for this information is most pronounced on days with earnings announcements, management guidance, and All-Star analyst reports. Surprisingly, demand does not increase at Form 10-K and Form 10-Q filings. While the overall demand for analyst estimates is 19.9 percent less than for analyst ratings and target prices, on earnings announcement and management guidance days, this preference is reversed. Moreover, the demand for analyst information substantially trumps that of SEC filings and financial statement information. JEL Classifications: M41; G14; G24.

We investigate the extent to which the provision by sell side analysts of cash flow forecasts incremental to earnings forecasts has an impact on the quality of Australian firms' financial reporting. Using three separate and distinct indicators of earnings quality, we consistently fail to find evidence of any improvement in the quality of financial reporting following analysts' provision of cash flow forecasts. There is some evidence that the impact on earnings quality is driven by the proportion of mining firms on the Australian Securities Exchange. Our results contrast with the argument by Healy and Palepu (2001) that sell side analysts play an important role in monitoring the quality of financial reporting but are consistent with the claim that sell side analysts' cash flow forecasts lack sophistication (Givoly et al., 2009).

We investigate three potential channels of analyst value creation: improving fundamental performance through monitoring, reducing information asymmetry, and increasing investor recognition. We show that changes in investor recognition have consistent explanatory power for the market reaction to coverage initiations and terminations but find mixed evidence for changes in information asymmetry and no evidence for changes in fundamental performance as determinants of the market reaction. These results suggest that analysts create value for firms under their coverage by improving their investor recognition and not by monitoring or reducing information asymmetry.

Li and You (this volume) study public firms’ common stock return reactions to two events: when analysts’ initiate coverage of the firm and when they terminate coverage. They test the returns for evidence of three sources of value added by analysts: (1) more monitoring of the firm, (2) reduced information asymmetry about the firm, and (3) greater demand for the firm’s common stock. They find consistent support for analysts adding value by increasing demand, but not monitoring or by reducing information asymmetry. Their findings also indicate that analysts’ initiations supply little new information. I review these findings, put them in perspective with related research, and note research directions.

Our study documents that the information content and the information processing of stock recommendations differ fundamentally between expansions and recessions. The initial market reaction to all recommendations is stronger in recessions, but “Buy” recommendations do not have long-term investment value. We find that in recessions sell side analysts are too optimistic about the stocks they recommend to buy, while investors initially overreact to these recommended stocks. In expansions, no such contradicting pattern exists. We also document that analysts favor “glamour” over “value” stocks irrespective of the state of the economy.

We examine a routine and timely disclosure, earnings press releases, to determine the extent to which several novel qualitative elements of such disclosures are associated with changes in sell-side financial analysts' information environment. Using a comprehensive set of GARCH-based (generalized autoregressive conditional heteroscedasticity) proxies, we examine how disclosure readability's components, across-document textual similarity, and within-document lexical diversity alter analysts' information environment. We find that readability in the form of shorter sentences, textual similarity, and lexical diversity are strongly related to decreases in analysts' uncertainty. Further, shorter sentences and lexical diversity improve both public and private information precision, whereas similarity affects solely analysts' private information precision. While the GARCH-based proxies allow us to alleviate concerns regarding potentially spurious inferences (Sheng and Thevenot 2012), we note as a caveat that such an estimation restricts our inferences to large, stable, and heavily followed firms. These findings should be of interest to analysts who may wish to explore the latent information contained within the qualitative elements of disclosure, regulators who direct the form and content of disclosure, and academics who study the use (and possible misuse) of various forms of information and its presentation.

Our objective is to penetrate the “black box” of sell-side financial analysts by providing new insights into the inputs analysts use and the incentives they face. We survey 365 analysts and conduct 18 follow-up interviews covering a wide range of topics, including the inputs to analysts’ earnings forecasts and stock recommendations, the value of their industry knowledge, the determinants of their compensation, the career benefits of Institutional Investor All-Star status, and the factors they consider indicative of high-quality earnings. One important finding is that private communication with management is a more useful input to analysts’ earnings forecasts and stock recommendations than their own primary research, recent earnings performance, and recent 10-K and 10-Q reports. Another notable finding is that issuing earnings forecasts and stock recommendations that are well below the consensus often leads to an increase in analysts’ credibility with their investing clients. We conduct cross-sectional analyses that highlight the impact of analyst and brokerage characteristics on analysts’ inputs and incentives. Our findings are relevant to investors, managers, analysts, and academic researchers.

We document that a stock's price around a recommendation or forecast covaries with prices of other stocks the issuing analyst covers. The effect of shared analyst coverage on stock price comovement extends beyond analyst activity days. A stock's daily returns covary with the returns of other stocks with which it shares analyst coverage. These links between stock price comovement and shared analyst coverage are consistent with the coverage-specific information we find in earnings forecasts; analysts who cover both stocks in a pair expect future earnings of the stocks to be more highly correlated than do analysts who cover only one stock from the pair. Collectively, our evidence indicates that analyst research produces coverage-specific spillovers that raise price comovement among stocks that share analyst coverage. The strength of these spillovers is comparable to spillovers from broad industry and market information in analyst research.

Although sell-side analysts often privately interact with managers of publicly traded firms, the private nature of this contact has historically obscured direction examination. By examining a set of proprietary records compiled by a large-cap NYSE-traded firm, I offer insights into which analysts privately meet with management, when analysts privately interact with management, and why these interactions occur. I also compare private interaction to public interaction between analysts and managers on conference calls. The evidence suggests that private interaction with management is an important communication channel for analysts for reasons other than firm-specific forecasting news

In this paper, I examine how the lending relationships between banks and their borrowers affect the quality of analysts’ earnings forecasts after financial deregulation in Japan. My findings show that short-term lending relationships improve the quality of analysts’ earnings forecasts and that these earnings forecasts are useful for predicting future returns. In contrast, long-term lending relationships decay the quality of forecast and are not valuable for the prediction of future returns. These empirical results indicate that the informational advantage that commercial banks acquire is short-term and that the costs of lending relationships surpass the informational benefits in the long run.

We study the joint effects of intercompany investing and reporting of equity method investments on the accuracy and dispersion of analysts' annual earnings-per-share (EPS) forecasts. We compare firm-year observations with and without equity method investments. We posit two non-mutually exclusive explanations for how equity method investments may affect analyst forecast properties. The Opacity Effect posits that the condensed equity method disclosures increase information asymmetry, increasing analysts' forecast errors and forecast dispersion. The Diversification Effect suggests that the diversification of the investor and its investee earnings streams enhances earnings predictability, decreasing analysts' forecast errors and forecast dispersion. Our findings are consistent with both effects operating in the analyst forecasting task. Additional analyses are consistent with the Opacity Effect dominating. This occurrence results, on net, in less accurate and more dispersed forecasts for firm-years with equity method investments. JEL Classifications: G14, M41

Using a comprehensive sample of investment recommendations, we investigate differences in the performance, behavior, and career outcomes of male and female sell-side analysts. Compared to their male counterparts, we find that the recommendations of female analysts produce similar abnormal returns but with lower idiosyncratic risks. Further, gender does not seem to negatively influence female analysts’ career outcomes as defined by their star rankings and job mobility among brokerage firms. In fact, being a female analyst seems to increase the likelihood of being listed among the prestigious Institutional Investor and WSJ star analysts.

This paper analyzes the Amihud (2002) measure of illiquidity and its role in asset pricing. It is shown first that the effect of illiquidity on asset pricing is clarified by using the turnover version of the Amihud measure and including firm size as a separate variable. When we decompose the Amihud measure into elements that correspond to positive (up) and negative (down) return days, we find that in general, only the down-day element commands a return premium. Further analysis of the up- and down-day elements using order flows shows that a sidedness variable, which captures the tendency for orders to cluster on the sell side on down days, is associated with a more significant return premium than the other components of the Amihud measure.

We document the determinants of the expectation heterogeneity of stock price forecasters on the TOPIX. Monthly panel data surveyed by QUICK Corporation in the Nikkei Group is utilized in the process. We examine the determinants of expectation heterogeneity by categorizing our sample into buy-side and sell-side professionals, and demonstrate that expectation heterogeneity arises as a result of the co-existence of different types of professionals within the same market. We show that the buy-side and the sell-side professionals, who have different business goals, differentiate the information contents as well as their interpretations of the same information in their forecasts, contributing to the expectation heterogeneity. In addition, we investigate the interactive expectations formulation of buy-side and sell-side professionals. We find that buy-side professionals incorporate the sell side’s ideas regarding the future stock prices into their own forecasts, although they exclusively refer to their own ideas when relating foreign exchange rates to the future stock prices. Meanwhile, sell-side professionals tend to utilize buy-side professionals’ ideas about future prices in order to improve their research and ingratiate themselves to their clients, i.e., the buy-side professionals. We demonstrate that this interactive expectations formulation also contributes to the generation of the expectation heterogeneity.

We study decisions to sell nonexcludable private information in the presence of a trading opportunity. Sell-side agents heighten competition among agents who buy their signals to combine with their own for proprietary trading purposes and thereby promote financial market efficiency. This result holds even when the sell-side production technology is not unique. But sell-side information is subject to underinvestment if producers do not internalize the benefits. The model suggests that fee-based compensation for corporate advisory services diminishes this problem and that market efficiency is undermined by forces steering investment-banking resources toward proprietary trading.

We examine the performance of buy-side institutional investor trades and sell-side brokerage analyst stock recommendations, as well as their interactions. Buy-side trades follow sell-side analyst recommendations but not the other way around. While buy-side purchases significantly outperform their sales, the difference in performance is largely concentrated on the day of the transaction. Following recommendation changes, buy-side trades in the same direction as the recommendation change earn the same returns as trades in the opposite direction. Therefore, institutional investors do not exhibit special skills in discerning the quality of recommendations.

This study investigates the influence of inferred valuation model use on the investment performance of sell-side equity analysts’ published price target opinions. There is limited and inconclusive evidence on how analysts’ price targets are determined and on their value for investment decisions. Using a broad sample of 45,693 price targets provided to First Call by sell-side analysts during 1997 through 2003, we first show that price targets have investment value because they predict future stock returns. Next, we develop and implement an innovative large-sample procedure for inferring valuation model use from the observed correlation between analysts’ price targets and two researcher-constructed stock valuation estimates that differ in simplicity and rigor. Reliance on a less rigorous valuation model may diminish the investment advantage associated with an analyst’s more accurate earnings forecasts but it may also mitigate the disadvantage of less accurate forecasts. We test whether the apparent use of a more rigorous valuation technique yields higher quality price targets as measured by realized investment returns over a 12-month horizon, controlling for possible differences in earnings forecast accuracy. The central message from our data is that price targets exhibit superior investment performance when analysts appear to be using a fundamental residual income (RIM) stock valuation technique rather than a simple price-earnings-growth (PEG) valuation heuristic. This investment advantage is reduced when analysts’ earnings forecasts are inaccurate. Our results underscore the importance of valuation model choice to analyst’s stock investment evaluation process.

We use proprietary data from a major investment bank to investigate factors associated with analysts’ annual compensation. We find compensation to be positively related to “All-Star” recognition, investment-banking contributions, the size of analysts’ portfolios, and whether an analyst is identified as a top stock picker by the Wall Street Journal. We find no evidence that compensation is related to earnings forecast accuracy. But consistent with prior studies, we find analyst turnover to be related to forecast accuracy, suggesting that analyst forecasting incentives are primarily termination based. Additional analyses indicate that “All-Star” recognition proxies for buy-side client votes on analyst research quality used to allocate commissions across banks and analysts. Taken as a whole, our evidence is consistent with analyst compensation being designed to reward actions that increase brokerage and investment-banking revenues. To assess the generality of our findings, we test the same relations using compensation data from a second high-status bank and obtain similar results.

We study the impact of social networks on agents’ ability to gather superior information about firms. Exploiting novel data on the educational background of sell-side analysts and senior corporate officers, we find that analysts outperform by up to 6.60% per year on their stock recommendations when they have an educational link to the company. Pre-Reg FD, this school-tie return premium is 9.36% per year, while postReg FD it is nearly zero. In contrast, in an environment that did not change selective disclosure regulation (the U.K.), the school-tie premium is large and significant over the entire sample period. CERTAIN AGENTS PLAY A KEY ROLE in revealing information to securities markets. In the equities market, security analysts are among the most important. A large part of an analyst’s job is to research, produce, and disclose reports forecasting companies’ future prospects, and to translate their forecasts into stock recommendations. Therefore, isolating how, or from whom, analysts obtain the information they use to produce their recommendations is critical. In this paper we investigate ties between sell-side analysts and management of public firms, and the subsequent performance of analysts’ stock recommendations. We exploit common past experiences, namely, attendance at the same educational institution, to identify firms where analysts are more likely to gain direct access to senior management. An advantageous aspect of our network ties is that they are formed long before the information likely being transferred across them, and thus the underlying tie (alumni link) is not directly related to the type of information likely being transmitted years later (company-related information).

Using NASDAQ reported individual stock level trading volume, we find that analyst research coverage on a stock increases an affiliated broker's market share of trading volume in that stock by 0.8 percent, on average, which corresponds to an additional annual volume of about one million shares in an average stock. Optimistic recommendations increase market share by an additional 0.4 percent, on average, which suggests that analysts have an incentive to issue upwardly biased recommendations. However, affiliated brokers receive more trading volume when recommendations are provided by analysts with better reputations and when analysts report new information to the market via coverage upgrades and downgrades. Furthermore, as the length of time during which an analyst maintains the same recommendation on a stock increases, the impact of the analyst's research coverage on the affiliated broker's market share of volume in the stock declines. The latter findings indicate that sell-side institutions are rewarded for high quality research services and for providing new information to the market.

We examine whether the quality differentials in earnings forecasts between reputable and nonreputable analysts vary with the severity of conflicts of interest. We measure personal reputation using the Institutional Investor All-American (AA) awards, and bank reputation using Carter-Manaster ranks. While both personal and bank reputation are associated with higher quality forecasts overall, their effectiveness against conflicts of interest differs. The severity of conflicts has a negative and significant effect on the performance of non-AAs at top-tier banks relative to other analysts, while it has a positive and significant effect on the performance of AAs at top-tier banks relative to others. Thus personal reputation is an effective disciplinary device against conflicts of interest, while bank reputation alone is not. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

The interaction between an investment bank's research and market making arms may have important implications for the trading of a firm's stock. We investigate the impact that research has on the liquidity provided by the bank's market maker. Utilizing a large sample of Nasdaq firms, we show that market makers whose banks also provide research coverage provide more liquidity and contribute more to price discovery than do market makers without such research coverage. Finally, we show that such “affiliated” market makers are less affected by uncertainty following earnings announcements. Our results provide new evidence on the sources of liquidity improvements for Nasdaq firms, and suggest that the information produced by banks in the sell-side research process is beneficial to their market makers.

The study reported here is a comparison of the earnings-forecasting performance of analysts at a large buy-side firm with the performance of sell-side analysts in the 1997–2004 period. The tests show that the buy-side analysts made more optimistic and less accurate forecasts than their counterparts on the sell side. The performance differences appear to be partially explained by the buy-side firm’s greater retention of poorly performing analysts and by differences in the performance benchmarks used to evaluate buy-side and sell-side analysts.

Because sell-side analysts are dependent on institutional investors for performance ratings and trading commissions, we argue that analysts are less likely to succumb to investment banking or brokerage pressure in stocks highly visible to institutional investors. Examining a comprehensive sample of analyst recommendations over the 1994–2000 period, we find that analysts’ recommendations relative to consensus are positively associated with investment banking relationships and brokerage pressure but negatively associated with the presence of institutional investor owners. The presence of institutional investors is also associated with more accurate earnings forecasts and more timely re-ratings following severe share price falls.

We examine the determinants and the informativeness of financial analysts' risk ratings using a large sample of research reports issued by Salomon Smith Barney, now Citigroup, over the period 1997-2003. We find that the crosssectional variation in risk ratings is largely explained by variables commonly viewed as measures of risk, such as idiosyncratic risk, size, book-to-market, and leverage. In addition, earnings-based measures of risk, such as earnings quality and accounting losses, also contribute to explaining the cross-sectional variation in the risk ratings. Finally, we document that the risk ratings can be used to predict future return volatility after controlling for other predictors of future volatility. We conclude that analysts play an important role as providers of information about investment risk.

We investigate the profitability persistence of the investment recommendations from analysts listed in four different star rankings, Institutional Investor magazine, StarMine’s “Top Earnings Estimators” and “Top Stock Pickers”, and The Wall Street Journal, and show the predictive power of each evaluation methodology. We found that only Buy and Strong Buy recommendations from the entire group of Star analysts outperform those of the Non-Stars in the year after election, while Sell and Strong Sell recommendations performed as those of the Non-Stars. We document that the highest average monthly abnormal return of holding a long-short portfolio, 0.97 %, is obtained by following the recommendations of the group of star sell-side analysts rated by StarMine’s “Top Earnings Estimators” during the period from 2003 to 2014. Since earnings are one of the main drivers of stock prices, the results obtained are in line with the notion that focusing on superior earnings forecasts is one of the top requirements for successful stock picks.

Research optimism among securities analysts has been attributed to incentives provided by underwriting activities. We examine how analysts’ forecast and recommendation optimism varies with the business activities used to fund research. We find that analysts at firms that funded research through underwriting and trading activities actually made less optimistic forecasts and recommendations than those at brokerage houses, who performed no underwriting. Optimism was particularly low for bulge underwriter firm analysts, implying that firm reputation reduces research optimism. There is also evidence that analysts at retail brokerage firms are more optimistic than those serving only institutional investors. We conclude that analyst optimism is at least partially driven by trading incentives.