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I study the effects of language commonality (i.e., sharing a native language) on information production in financial markets. Using a hand-collected data set on the prevalent dialects for 2,091 cities (counties) in China, I identify the effects of language commonality separately from those of shared hometown and geographic proximity. In in-sample tests, language commonality between analysts and CEOs increases the return of trading on analysts’ recommendations by 5.5%. The results mainly stem from less intelligible dialects. Broadly speaking, language commonality can alleviate communication frictions when nonnative languages are used in professional settings. This paper was accepted by Gustavo Manso, finance.

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.

PurposeThis paper investigates individual investors' responses to stock underpricing and how their trading decisions are affected by analysts' forecasts and recommendations.Design/methodology/approachThis empirical study uses mutual fund fire sales as an exogenous source that causes stock underpricing and analysts' forecasts and recommendations as price-correcting information. The study further uses regression analysis to examine individual investors' responses to fire sales and how their responses vary with price-correcting information.FindingsThe authors first show that individual investors respond to mutual fund fire sales by significantly decreasing net buys, and this effect appears to be prolonged. Next, the authors find that the decrease of net buys diminishes following analysts' price-correcting earnings forecast revisions and stock recommendation changes. Hence, the authors suggest that individual investors are not “wise” enough to recognize flow-driven underpricing; however, this response is weakened by analysts' price-correcting information.Originality/valueThere is an ongoing debate in the literature about whether individual investors should be portrayed as unsophisticated traders or informed traders who can predict future returns. The authors study a unique information event and provide new evidence related to both perspectives. Overall, our evidence suggests that the “unsophisticated traders” perspective is predominant, whereas a better information environment significantly reduces individual investors' information disadvantage. This finding could be of interest to both academic researchers and regulators.

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.

We examine the relation between accounting reporting complexity and analysts’ performance and whether analysts’ qualifications, experience, and expertise in specific financial domains help them more effectively process complex information. We document an inverse relation between complexity and analysts’ performance. Further, we show that analysts’ firm-specific experience, industry focus, and CFA certification alleviate some of the adverse effects of complexity, whereas analysts’ general experience does not appear to do so. Using an XBRL-based approach, we also develop new measures of analysts’ expertise and find that expertise in the areas of fair value, derivatives and pension are more valuable than other analyst characteristics in attenuating the negative effects of complexity arising from transactions and events in these areas. Overall, this study underscores the importance of analyst characteristics and the need to simplify the complex disclosures in the notes to the financial statements.

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 investment banks, brokerage houses, and pension funds spend large amounts of capital to hire security analysts to predict earnings, stock recommendations, and target prices for their customers and public investors. These observations raise a compelling empirical motivation for the researcher to investigate Do Sell-Side Security Analysts (SSSA) can forecast earnings, stock recommendations, target prices, and particularly consensus prices (average target prices) accurately. The population of the study includes public listed companies in Colombo Stock Exchange which are of interest to the SSSA in their equity research studies but all the listed companies cannot be considered as the population since there are companies that haven't used in the stock market research or equity research studies of the brokering firms. The number of companies qualifying for the study is based on the sample selection criteria to limit the analysis to a realistic level. There are 22 listed companies, qualified for the study from 2012 to 2018. In calculating monthly stock returns, the researcher assumes that any form of declaration of remittances such as dividends, bonus issues, stock splits, and right issues encourage investors to purchase the stock and it causes the price of a stock to increase. In general, the increase is about equal to the amount of the benefit, however, the actual price change is based on market activity. Finally, the results of hypothesis testing through multiple regression models discuss to achieve the research objectives. The findings of the study have important implications for diverse users to formulate their future policy decisions for the development of the stock market and the economy. The investigation reveals that there is a statistically significant positive relationship between Rit and RCP.

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 ...

We study sell‐side analysts’ motives to diversify their portfolios across industries. Despite the negative association between diversification and accuracy, more than 60% of analysts cover multiple industries. We argue that analysts’ choice to diversify is rooted in concerns about future job security. We find that more diversified analysts are less likely to experience job turnover and leave the profession but are not more likely to advance their careers. For experienced and all‐star analysts, diversification does not improve career outcomes. We conclude that industry diversification is a safety mechanism for inexperienced and unranked analysts who are concerned about job security.

Purpose This paper aims to investigate how sell-side analysts form expectations on, analyse, and communicate the effects of corporate acquisitions. Design/methodology/approach The paper reports on case studies of three listed firms who are frequent acquirers. The case data comprise semi-structured interviews and content analysis of analyst reports and corporate reports. Findings The paper reports three sets of findings. First, the analysts viewed acquisitions as heterogeneous events and, therefore, also treated acquisitions differently depending on factors such as size and acquisition strategy and the perceived “authenticity” of the acquisition (i.e. whether parts of the acquisition would be more accurately described as organic growth and regular capital expenditure (CAPEX) investments). Second, the authors find that analysts struggle with analysing the effects of acquisitions at the announcement date because of a mismatch between the analysts’ need of and the analysts’ access to relevant information. Although clients demand evaluations of announced acquisitions, relevant accounting information is not published until much later and the information at hand only allows for cursory analyses. Finally, the authors find that the analysts’ valuation models were too inflexible to fully incorporate the effects of the acquisition. In sum, the analysts, therefore, developed acquisition-driven investment cases without supporting accounting information and without converting expected acquisitions into forecasts. Originality/value By adopting a qualitative case study research design, the paper contributes to the ongoing efforts to open the “black-box” of sell-side analyst behaviour. In particular, the unique research design focusses on effects related to specific corporate events (acquisitions) rather than analysts’ everyday work.

PurposeThe purpose of this paper is to examine the influence of financial restatements on the sell-side analysts' stock recommendations.Design/methodology/approachThe sample of this study is based on a dataset from a panel of 246 Malaysian public listed companies for the period 2008 to 2013 (651 company-year observations). This study employs feasible generalized least squares regression.FindingsThis study finds a negative and significant relationship between restated companies and sell-side analysts' stock recommendations, which means that sell-side analysts issue less favorable stock recommendations for restated companies.Practical implicationsThe findings based on observations from an emerging economy complement the results of the US studies that analysts revise their earnings forecasts or recommendations downwards or drop coverage following financial restatements. The results of this study should be useful to capital market participants in understanding how analysts perceive and evaluate restated companies.Originality/valueThis paper expands the literature on financial restatements consequences in an emerging market which is largely unstudied. Prior research on analyst behavior towards restatements has focused on the consequences of restatements in terms of analyst following and forecast accuracy and dispersion. This study examines if and how the restatements affect the analysts' final output as reflected in the recommendation opinion, an area that has so far received little attention.

We investigate whether earnings forecasts issued by sell-side analysts are incrementally informative about the returns of firms listed on the Warsaw Stock Exchange (WSE), a moderately-developed, postcommunist capital market. Our sample covers the fiscal years 2008-2016. The informativeness of earn- ings (and earnings forecasts) is defined as the association between earnings (earnings forecasts) and returns. Our findings indicate that the mean earnings forecasts issued by sell-side analysts are incremen- tally informative about firm returns beyond the earnings reported. This result does not depend on firm size, profitability, or market return. The findings indicate that such forecasts incorporate useful incremen- tal valuation information and that the incremental informativeness of these forecasts serves to protect the interests of analysts’ clients.

Target prices are often provided as a support for stock recommendations by sell-side analysts which represent an explicit estimate of the expected future value of a company’s stock. This research focuses on mean target prices for stocks contained in the Standard and Poor’s Global Clean Energy Index during the time period from 2009 to 2020. The accuracy of mean target prices for these global clean energy stocks at any point during a 12-month period (Year-Highest) is 68.1% and only 46.6% after exactly 12 months (Year-End). A random forest and an SVM classification model were trained for both a Year-End and a Year-Highest target and compared to a random model. The random forest demonstrates the best results with an average accuracy of 73.24% for the Year-End target and 81.15% for the Year-Highest target. The analysis of the variables shows that for all models the mean target price is the most relevant variable, whereas the number of target prices appears to be highly relevant as well. Moreover, the results indicate that following the rare positive predictions of the random forest for the highest target return groups (“30% to 70%” and “Above 70%”) may potentially represent attractive investment opportunities.

Due to the characteristics of high leverage and low margin, option is very suitable for quantitative trading by applying portfolio management to control the profit and risk. The money management is an important issue to build a portfolio especially for option sell-side trader, since the profit is only the premium, while the loss is unlimited. In this research, we propose a model for option sell-side strategy to estimate the win-rate of option by the premium, time to maturity, and volatility based on statistical approach and random forest algorithm. The prediction of the model is visualized through heatmap which can reveal the profitable trading range intuitively, we use the precision score to evaluate the performance in these two models and proof the effectiveness and robustness of predictive model proposed by random forest algorithm. In the future, we plan to apply other machine learning algorithm to propose the predictive model for spread trading.

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.

We examine whether highly reputed sell-side analysts (Stars) account for stock market seasonality in their forecasts. Extensive research has documented that seasonality exists in the stock market, ...

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.

Os vieses comportamentais são caracterizados por situações recorrentes, em que os indivíduos tomam decisões, utilizando-se de heurísticas (regras de bolso), fazendo com que tenham escolhas equivocadas ou mesmo diferentes do que seria esperado pela teoria tradicional de finanças, em que os indivíduos são racionais e resolvem racionalmente determinada situação. O efeito disposição é um desses vieses e se caracteriza pelo comportamento, que faz com que os investidores vendam posições vencedoras em uma proporção maior do que as posições perdedoras, o que tende a prejudicar a rentabilidade dos seus portfólios. A origem desse viés encontra sustentação na literatura e pode estar relacionada aos fundamentos da Teoria do Prospecto, da contabilidade mental, da aversão ao arrependimento, da pressão social, de questões relacionadas ao autocontrole dos indivíduos e da interpretação equivocada do viés de reversão à média. Independentemente da sua origem e explicação, o fato é que existe vasta literatura que documenta sobre o viés, em investidores individuais, institucionais ou em gestores de fundos. Além disso, há inúmeros estudos que mostram que o efeito disposição é maior em investidores individuais do que em investidores institucionais e gestores de fundos. Assim, uma contribuição relevante esperada para a literatura é que esta pesquisa analisou o viés em um público até então pouco estudado. O objetivo do presente estudo foi investigar se o efeito disposição também impacta os profissionais de sell side, que realizam recomendação de carteira de ações no Brasil. Os profissionais de sell side são responsáveis por fazerem recomendação de ações, para auxiliar os clientes das corretoras na montagem dos seus respectivos portfólios. Para o estudo, utilizou-se o banco de dados da Carteira Valor, divulgado pelo Jornal Valor Econômico, que compartilha mensalmente, desde 2012, as ações mais recomendadas de corretoras brasileiras. Foram realizados estudos com a própria Carteira Valor, que é uma carteira teórica, composta pelas ações mais recomendadas e com os dados de sete corretoras, analisados de forma individual e agregada. Para verificar a existência do viés, calculou-se a Proporção de Ganhos Realizados e se subtraiu a Proporção de Perdas Realizadas, submetendo-se os resultados a um Teste de Diferença entre Proporção. Os resultados se mostraram estatisticamente significativos, a um nível de significância de 1%, e apontam que os profissionais de sell side não apresentaram o efeito disposição nas suas recomendações. O resultado da pesquisa contribui para o estudo do efeito disposição e levanta algumas questões que podem ser objeto de estudos futuros: o motivo pelo qual os profissionais de sell side não apresentam o viés e se a ausência do viés faz com que as suas recomendações sejam superiores em performance dos gestores de fundos que apresentam. Behavioral biases are characterized by recurrent situations that individuals make decisions using heuristics (pocket rules), taking wrong or even different decisions than would be expected by traditional theory finance, in which individuals are rational and make rational decisions. The effect disposition is one of these biases and is characterized by the behavior that makes investors sell winning positions in a greater proportion than the positions losers, which harms the profitability of their portfolios. The origin of this bias finds support in the literature and may be related to the basis of Prospect Theory, mental accounting, aversion to regret, social pressure, of issues related to individuals’ self-control and misinterpretation of the bias of reversion to the average. Regardless of its origin and explanation, there is vast literature that documents the bias whether it is in individual, institutional investors or in fund managers. In addition, there are numerous studies showing that the effect disposition is greater for individual investors than for institutional investors and fund managers. However, despite numerous studies, most of them is related to individual, institutional investors, and fund managers, so a relevant contribution to the literature is that this study analyzed the bias in a public hitherto little studied. This paper aimed to investigate whether the disposition effect also impacts health professionals sell side who carry out recommendation stock portfolio in Brazil. Health professionals sell side are responsible for making recommendation of actions to assist brokers’ clients in setting up their respective portfolios. We used the database of Valor Portfolio, which was published by Valor Econômico newspaper, the one that has been publishing monthly since 2012 the most recommended actions by Brazilian brokers. Studies have been carried out with the Value Portfolio, which is a theoretical portfolio composed by the most recommended shares and with data from seven brokerages, analyzed individually and in aggregate. To check the existence of bias, the Proportion of Gains was calculated and subtracted the Proportion of Losses, subjecting the results to a Difference Test between Proportion. The results proved to be statistically 1% significant and point out that health professionals sell side did not show the disposition effect in their recommendations. The research result contributes to the study of the disposition effect and raises some questions that may be the subject of future studies: the reason why professionals in sell side do not present the bias and if its absence makes their recommendations superior in performance of the fund managers they present to.

Impacts of high-frequency trading (HFT) on market quality and various actors have been broadly studied. However, what happens when HFT is not a prominent figure in a market remains relatively unexplored. The paper seeks to answer this question focusing on 30 blue chip stocks in an emerging market, Borsa Istanbul, through Dec 2015 to Mar 2017. Despite a low share in the overall activity, HFT has observable effects: liquidity provision by non-HFT traders significantly reduces with HFT; HFT activity on the sell side induces higher volatility; and HFT generates profits on both positive and negative return days. These findings raise concerns regarding HFT and show potential externalities are not specific to the markets with HFT dominance.

This study examines whether foreign investors affect the information production of analysts. Based on China’s stock market, we find that foreign investors significantly reduce analysts' coverage. Such negative association is more pronounced in firms with a high level of governance and information disclosure and varies with analyst characteristics. Further tests suggest that as foreign investors crowd out analysts, the number of research reports and brokerage' site visit fell, but analyst forecast accuracy improved, indicating that the demand and supply of information are generally in equilibrium. We further address the endogeneity issue using a quasi-natural experiment, the “Shanghai-Hong Kong Stock Connect”, and the results still hold. Overall, our results present evidence of potential information production by foreign investors, providing policy implications and highlighting the positive effect of China’s open-door policy in capital markets.

We study whether and how sell-side research affects the agency issue between asset managers and their clients. We show that even if sell-side research alone does not generate conflicts of interest, it can exacerbate the moral hazard problem of asset managers. Imposing transparency on the use of sell-side research, as the recent regulation MiFID II does, helps investors alleviate this negative effect. Forcing the managers to absorb sell-side research costs has a similar effect. Our model explains the empirical findings on how transparency affects the supply of buy-side research, the demand for and the quality of sell-side research. This paper contributes to improving the organization of the asset management industry and the debate on recent regulations on sell-side research.

Sell-side analysts commonly transition to buy-side money managers. I examine whether these career transitions compromise sell-side research, relying on granular career information of 6,310 analysts. I find that these analysts issue recommendations that favor their future buy-side employers during the year immediately before the transition. This favoritism is more pronounced among stocks where a single analyst is more impactful and is present only among transitions likely to be strategically planned. Additional analyses using target price forecasts reveal that these optimistic forecasts are less accurate. The findings suggest that these career transitions are a new source of conflicts of interest.

The story told here is of conflict of interest in equity research. When researching a company, an equity analyst may be swayed, in this case through perceived friendship, by the management of that company. An equity analyst has the obligation to give objective and honest recommendations to clients. I use virtue ethics to explain why we have this obligation and why it is important to act virtuously in circumstances similar to the one I experienced in my plantation adventure.

I empirically study how confirmatory bias works for strong and contradictory signals using data on sell-side analysts. I first model an agent who is prone to confirmatory bias and whose task is to value a stock based on a signal, and introduce the effects of the signal strength by relaxing Rabin and Schrag's (1999) assumption of a constant bias severity. Afterwards I use target prices to measure forecast bias and the growth in Earnings Per Share as signals, and regress analysts' forecast bias over different deciles of favorable signals interacted with prior negative forecast bias in a dynamic panel data model. I find that analysts do not react positively to favorable signals when the prior is pessimistic, except for sufficiently strong signals which cause analysts to issue more optimistic target prices.

In this paper we test the hypothesis that sell recommendations are costlier than buy recommendations by carrying out cointegration analyses. We find that that analyst recommendations that plainly urge the investor to take action (buy, sell) are consistent with their estimated losses (gains). Importantly, we find that analysts react mildly to higher projected losses, and strongly to higher projected capital gains. Also, we find that higher projected losses are positively related to dispersion in analysts' recommendations. In summary, we find empirical evidence in favor of Womack's (1996) hypothesis that the cost of issuing a sell recommendation is greater than the cost of a buy recommendation.

It is well known that heuristics affect people’s judgment within virtually every setting. We find that heuristics exert a strong and positive influence on the sell-side analyst writing process (broadly referred to as the “judgment process”) and that the interaction between detail (as defined) and overconfidence and between detail and tone strongly influence the sell-side analyst judgment process. We also find that decision-makers respond to these attributes. We assess how recommendations in sell-side analysts’ reports trigger decision-makers to trade by measuring trade volume. We apply canonical corrections to support our findings, as we believe that an individual’s judgment process is based on a set of outcome variables. Although the explanatory power of our results may seem low, they enhance our understanding of how sell-side analysts process soft and hard information.

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.

Data mining is quite common in econometric modeling when a given dataset is applied multiple times for the purpose of inference; it in turn could bias inference. Given the existence of data mining, it is likely that any reported investment performance is simply due to random chance (luck). This study develops a time-series bootstrapping simulation method to distinguish skill from luck in the investment process. Empirically, we find little evidence showing that investment strategies based on UK analyst recommendation revisions can generate statistically significant abnormal returns. Our rolling window based bootstrapping simulations confirm that the reported insignificant portfolio performance is due to sell-side analysts’ lack of skill in making valuable stock recommendations, rather than their bad luck, irrespective of whether they work for more prestigious brokerage houses or not.

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.

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.

We employ the vessels that comprise the dry bulk segment of the maritime industry and examine how market sentiment affects the herding behavior of shipping investors in a real asset market. Our results show that the behavioral aspect of investing, measured through intentional and unintentional herding, contrary to the results for financial markets, is affected by sentiment on the buy side (newbuildings) but not on the sell side (scrapping). Furthermore, we provide evidence that when market sentiment is negative, investors tend to follow market leaders (intentional herding), while, when sentiment is positive, unintentional herding leads to common investment practices among shipping investors. Our results have significant implications both for academics and for practitioners since they reflect a clear distinction of the pattern of investment decisions for real assets, compared to financial assets.

We present two stock recommendation systems based on stochastic characterization of firm present value that extends the conventional discounted cash flow analysis. The single-stock quantile recommendation system compares the market price of a company's stocks with the estimated distribution of the company's fair value to obtain an individual measure of mispricing, while the cross-sectional quantile system builds a relative measure of mispricing using the fair-value distribution of all firms. Both systems use mispricing information to build sell side and buy side portfolios. Statistical tests show that these portfolios consistently deliver significant excess returns even when rebalancing costs are accounted for. Moreover, we show how analysts' indications can be improved by using the first two moments of their recommendations following the same procedure of the cross-sectional quantile system.

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.

This study conducts a comprehensive investigation into the investment value of sell-side analyst recommendation revisions in the UK, using a unique dataset from 1995 to 2013. Our rolling window analysis shows that, on average, upgrades fail to generate any sig-nificantly positive abnormal returns in any period of time, even before transaction costs. In addition, although downgrades could generate significantly negative abnormal gross returns over some periods of time, these observed significant returns disappear after accounting for transaction costs. Overall, our bootstrapping simulations confirm sell-side analysts’ lack of skill in making valuable up/downward revisions to cover the size of trans-action costs, irrespective of whether these revisions are made by high-ranking brokerage houses or not. However, an industry-based analysis shows that, within two high-tech indus-try sectors, i.e., Health Care and Technology sectors, sell-side analysts possess certain skill in making valuable downgrades over some periods of time and, in particular, such skill is sufficient to offset transaction costs.

This paper examines how institutional investors interact with sell-side analysts in Korean stock market. I focus on the role of institutional investors as sophisticated stock market participants who may analyze sell-side analysts` information components as earnings forecast in addition to using their outputs as recommendation, target price. Furthermore, I examine whether institutional investors can differentiate good information from bad information provided by sell-side analysts. By using a sample of 1,421 firm/year observations in Korean stock market from 2001 to 2011, the results indicate that institutional investors may take an active role as a mechanism to incorporate V/P ratios (value to price) derived from earnings forecast information to analyze sell-side analysts` information components as earnings forecast, in addition to using the outputs as Recommendation. Moreover, I find that institutional investors are more likely to use sellside analysts` information only when the earnings forecast is more accurate, meaning that institutional investors can differentiate the good information from bad information. On the other way round, I examine if institutional investors` trading behavior affect the sellside analysts` information, and find that sell-side analysts do not use information produced from buy-side investors` trading behavior. In sum, I can conclude that the main results support the causality relationship that institutional investors trade by looking at the sell-side analysts` information components as earnings forecast in detail, and by using their information only when the earnings forecast information is more accurate, not the other way round. This study can shed some lights on the knowledge about the unobserved interaction between the most sophisticated stock market participants who are considered to have taken a role to enhance stock market efficiency, and extend the prior literature which factors bring about institutional investors` sophistication.

Asymmetric information, investor optimism, and unbiased prices hypotheses are the main hypotheses proposed for explaining how investors’ difference of opinion may impact stock returns. We use a new measure for divergence in investor beliefs among sell-side analysts to test these three hypotheses. Our initial findings are not supportive of either the asymmetric information or the investor optimism hypotheses. However, since these two hypotheses predict opposing effects of divergence in opinion on stock returns, the effects could neutralize their respective impacts on stock prices. Our further empirical analysis though suggests that this is not the case. The weight of the evidence presented suggests thatwithin the sell-side, the difference of opinion does not impose a bias on future stock returns.

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.